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The proton exchange membrane fuel cell (PEMFC) air supply system is a complex nonlinear system with strong coupling of air flow and pressure. To avoid oxygen starvation and unstable output performance during rapid load changes, the oxygen excess ratio (OER) and air pressure need to be controlled effectively. To cope with the nonlinearity, coupling and uncertainty of the PEMFC air system, this paper puts forward a coordinated controller regulating OER and air pressure based on the input-output linearization and sliding mode methods. Firstly, a control-oriented third-order model is proposed to describe the dynamic behavior of the air supply system. Secondly, this paper decouples the flow and pressure of the PEMFC air system by using an input-output linearization method to obtain two independent linear subsystems. Moreover, a sliding mode method, effectively coping with the uncertainty of the system model, is designed to regulate the OER and air pressure of the PEMFC, which enhances the robustness of the control system. The overall simulation outcomes show that the proposed controller regulates OER and cathode pressure with smaller root mean square error (RMSE) and mean absolute percentage error (MAPE) compared with the combined proportional integral (PI) and feedforward controller. • A modified model oriented to control of air supply system is proposed. • Input-output linearization and sliding mode are used to develop coordinated control strategies. • The outcomes illustrate that the air supply affects the output performance of the fuel cell. • Control performance in the presence of model uncertainty is verified. [ABSTRACT FROM AUTHOR]

To address the trajectory tracking issue of upper-limb rehabilitation exoskeleton with uncertainties and external disturbances, this paper proposes a fractional-order ultra-local model -based model-free finite-time robust controller (FO-FTRC) using predefined performance sliding surface. Different from previous model-free control strategies, a novel multi-input multi-output (MIMO) fractional-order ultra-local model which is a virtual model is proposed to approximate the complex uncertain nonlinear exoskeleton dynamics in a short sliding time window. This allows the design of controller to be independent of any exoskeleton model information and reduces the difficulty of controller design. The developed robust model-free control method incorporates a fractional-order quasi-time delay estimator (FO-QTDE), unknown disturbance estimator (UDE) as well as prescribed performance sliding mode control (PPSMC). The FO-QTDE is utilized to estimate the unknown lumped uncertainties which employs short time delayed knowledge only about the control input. However, the low-pass filter is always added for FO-QTDE when disturbances change fast, which leads to unavoidable estimation error. Then, UDE is designed to further eliminate the estimation error of FO-QTDE to enhance control performance. The PPSMC is constructed to converge sliding surface to zero in a finite time. Besides, the sliding surface is always limited in performance boundaries. After that, the overall system stability and convergence analyses are demonstrated by using the Lyapunov theorem. Finally, with the comparison to other methods of α -variable adaptive model free control (α -AMFC), time-delay estimation-based continuous nonsingular fast terminal sliding mode controller (TDE-CNFTSMC), time delay estimation (TDE)-based model-free fractional-order nonsingular fast terminal sliding mode control (MFF-TSM) and fractional-order proportion–differential (PD β), the co-simulation results on 7-degree-of-freedom (DOF) iReHave upper-limb exoskeleton virtual prototype and experiment results on 2-DOF upper-limb exoskeleton are obtained to illustrate the effectiveness and superiority of the proposed FO-FTRC method. • A fractional-order ULM is proposed to approximate complex exoskeleton to achieve MFC. • A QTDE and disturbance estimator is designed to eliminate the lumped uncertainties. • The paper achieves the FT stabilization under fractional-order ULM design framework. • The co-simulation experiments on 7-DOF iReHave exoskeleton and experiment on 2-DOF. [ABSTRACT FROM AUTHOR]

ESA Solar Orbiter was launched from Cape Canaveral in collaboration with NASA on the February 10, 2020 to start its journey around the Sun, with the commissioning phase ending in April 2020. After commissioning, ESA set a tighter pointing requirement goal to further improve the performance in Fine Pointing Mode, in preparation of the upcoming start of Science Phase. The first part of this paper outlines the end-to-end process which allowed - in just six months – to update the Fine Pointing Mode Design, re-tune the controller with refined assumptions taken from flight data and robust methods and execute full validation of the new AOCS Software on the Avionics Test bench at Airbus Defence and Space. The second part of the paper describes the upload in flight of the new Software and the analysis of the on-orbit pointing performance, which showed a significant improvement with respect to the previous one, thus contributing to the success of the Mission's scientific goals. • Solar Orbiter Payload Instruments required a better pointing jitter performance (Relative Pointing Error) after launch • Root cause analysis on flight telemetry to identify driver contributors to pointing error • Fine Pointing Mode controller design and tuning updated with refined inputs based on flight data and with robust control methods • Controller uploaded in flight significantly improved the Spacecraft pointing performance [ABSTRACT FROM AUTHOR]

This paper proposes a reasonable, practical, and novel method for designing a robust controller for two degrees of freedom nano-electromechanical scanners based on the combination of quantitative feedback theory (QFT) and the Taguchi method. Although the main primary of this paper devotes to rotational control, an investigation of two-degree freedom (rotational/bending) is studied by employing the Taguchi method. A moveable main plate suspended by two nano-beams over a fixed substrate electrode is used to represent the scanner. The nanoscanner is thoroughly analyzed using the most comprehensive modeling design, considering the elastic, electrical, Casimir force and moment, and squeezes film damping. The nanoscanner's governing equations are initially derived by considering both rotation and deformation. In addition, because the size dependency of materials is significant in ultra-small structures, we developed the constitutive equations within the context of the modified couple stress theory to integrate the effect of scale dependency. Next, system uncertainties have been wholly addressed to achieve an accurate model. As a result, using robust control methods such as quantitative feedback theory to precisely control nano-scanners in the presence of uncertainties is inevitable. The quantitative feedback approach transforms the nonlinear plant into a family of linear uncertain plants in the first part. This is accomplished using a fixed-point theorem, after which appropriate disturbance rejection boundaries are discovered. In this problem, quantitative feedback controllers and checking the system's stability at any frequency and time are intended to solve the tracking problem and the disturbance rejection issue. Due to the uncertainty associated with the system model's complexity and accuracy, we employ a QFT controller to control the system. Moreover, because this system has only one input and two outputs, and changing the controller's gain is complicated, the Taguchi method has been employed to enhance better performance. Nonlinear simulations of the tracking issue are carried out, and the results demonstrate the effectiveness of the developed controllers and prefilters. The findings show that using the suggested approach effectively overcomes the challenges to robust control of a nonlinear rotational nanoscanner, and also the system achieves the best angle and deflection adjustment accuracy. [Display omitted] • Mathematical modeling of a Torsion/Bending of Rotational Nanoscanner and comparing control method with experimental data. • If a user inputs erroneous voltage to reach system's output, the control approach automatically corrects the system input. • Designing SIMO (Single Input Multi Output) robust controller using Taguchi Method in the presence of uncertainties. • Modifying controllers in a system using the Taguchi method ensures stability and output without adverse effects. • Nonlinear simulations of the tracking issue are carried out, and the results shoe the effectiveness of the developed method. [ABSTRACT FROM AUTHOR]

• The 6-DOF attitude-orbit coupled model of SFF is established. The model has no redundant state and can be achieved globally without singularity. • A FxTDO is developed to estimate the external disturbance. Any prior knowledge of the disturbance is not required. The estimation error of the disturbance can converge to zero in fixed time regardless of the initial states. • A composite control scheme which consists of the NFFTSM surface and a feed-forward term based on the FxTDO is proposed such that each follower spacecraft can track the desired positions and attitudes in fixed time. This paper presents a distributed fixed-time control protocol for 6-DOF(degree-of-freedom) attitude-orbit coupled spacecraft formation flying with external disturbances. Firstly, the 6-DOF attitude-orbit coupled dynamics is established. The communication topology between the spacecraft in the formation is described by a directed graph. Secondly, a fixed-time disturbance observer (FxTDO) is designed to ensure that the estimation errors of the unknown external disturbances can converge to zero in fixed time. Thirdly, based on non-singular fixed-time terminal sliding mode (NFFTSM) surface, the fixed-time coordination control protocol is proposed combined with the fixed-time disturbance observer, which can guarantee that each spacecraft can track their desirable positions and attitudes in fixed time. The stability of the closed-loop system is proved through Lyapunuov method. Finally, simulation results for a formation with one virtual leader and five followers demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

The agility of satellites equipped with large and flexible structures, such as solar panels or antennas, poses a significant challenge due to the influence of elastic dynamics on attitude motion. This results in reduced pointing accuracy and dimensional stability of the payload. To address this issue, an Active Collocated Attitude Control (ACAC) system has been developed, utilizing actuators for both the elastic dynamics (distributed piezoelectric devices) and attitude control (ON-OFF thrusters). In the initial phase of the project, the algorithm underwent extensive verification using a high-fidelity numerical model of a spacecraft with two very-low frequency flexible solar panels and a payload consisting of two long booms and a transversal antenna's reflector. The paper focuses on the second phase of the project, which revolves around the experimental verification of the control architecture concept. To achieve this, a scaling procedure employing the dynamic analogy approach was implemented to determine the design parameters of a free-floating platform equipped with elastic appendages. This ensured that the resulting elastic multibody system displayed similar dynamic behavior to the full-scale satellite. Based on the scaling parameters, a test rig was manufactured, and actuators and sensors were optimally positioned. The performance of the ACAC system was then compared to that of traditional benchmark controllers. The results show that the ACAC system demonstrates superior capabilities in performing fast slew maneuvers without developing unstable interactions with the elastic dynamics. • Agile maneuvers of large satellites could excite rigid-flexible interactions. • A robust control of attitude and elastic dynamics is implemented to improve agility. • Performance obtained with numerical models is verified with scaled-down test-rig. • Simplified dynamic equations are developed to determine scaling conditions. • Experimental results of the robust control are consistent with simulation. [ABSTRACT FROM AUTHOR]

This paper concentrates on robust attitude control issues for spacecraft formation in gravitational-wave detection missions. Notably, with the large-scale communication delays brought by the million kilometers-scale inter-satellite distance, the exponential convergence of the closed-loop delayed system is firstly achieved via a new delay-dependent nominal attitude coordinated control scheme. Then, a finite-time disturbance observer is deployed to reconstruct the unknown lumped disturbance from internal uncertainties and the external environment. Meanwhile, an integral sliding manifold is embedded in the delay-dependent attitude controller for superior systems' robustness. Finally, two simulation examples illustrate the feasibility and effectiveness of the proposed attitude control strategy for in-orbit gravitational-wave detection spacecraft systems. • Spacecraft formation attitude control in gravitational-wave detection is studied. • Large-scale communication delays (LCD) among formation members are firstly modeled. • An attitude coordinated controller is put forward to handle the LCD. • An integral sliding manifold with disturbance observer is embedded for superior robustness. [ABSTRACT FROM AUTHOR]

Uncertainty can lead to jitter or overshoot in mechanical systems, necessitating the design of multiple constraints to stabilize them. This paper proposes a control structure based on the generalized Udwadia–Kalaba equation to address these constraints simultaneously. An uncertain dynamical model is developed, incorporating both equality and inequality constraints. By integrating diffeomorphism theory, a robust control strategy is designed to ensure compliance with these constraints. Utilizing the Lyapunov approach, the uniform boundedness and uniform ultimate boundedness of the dynamical system are demonstrated. Finally, the feasibility of the proposed control method is validated through its application to a belt conveyor system. • Equality constraints and inequality constraints are simultaneously considered in dynamical system based on the generalized Udwadia–Kalaba approach. • A robust control for handling inequality constraints that does not affect equality constraints is designed. • The robust control can render the uncertain system uniformly bounded and uniformly ultimately bounded. • The method is proposed of applying inequality constraints to belt conveyors to avoid belt breakage and folding faults in engineering. [ABSTRACT FROM AUTHOR]

Today, hydrogen fuel cells (HFCs) have become very popular in various applications because of their ability to be a clean energy source. One of the difficulties associated with HFCs is their sluggish response to variations in the load. This paper presents a nested control strategy based on a type-2 neuro-fuzzy controller (T2NFC) to improve the HFC's dynamic response in a hybrid stand-alone power network using HFC and battery. A system model is constructed using Matlab-Simulink. An interleaved converter is used to draw the maximal power from the HFC and reduce the ripple in the HFC's current. Two T2NFCs control DC voltage and battery charge/discharge current. The robustness of the T2NFC is evaluated for input disturbance, output disturbance, and both disturbances. The results show that the proposed control strategy is robust against input and output disturbances. Also, it provides improved dynamic response of the HFC, lower ripple in HFC current, and less overshoot or undershoot in DC voltage both in transient and steady-state. For step reference input, the proposed controller improves settling time of 24.06 % and overshoot of 59.55 % compared to the conventional PI controller. The results verify the effectiveness of the proposed controller under different operating conditions of hybrid stand-alone power network with fuel cell and battery. • The response of HFC is enhanced, leading to faster and more accurate power generation. • The hydrogen fuel cell's current is experienced a significant reduction in ripples. • The hydrogen fuel cell is now being operated at its maximum power point. • A Type-2 Neuro-Fuzzy Controller is developed to provide robust control of the hydrogen fuel cell's output voltage. [ABSTRACT FROM AUTHOR]

In this paper, an anti-unwinding adaptive robust backstepping control law is proposed to solve the attitude control problem of rigid spacecraft with external disturbances and inertia uncertainties. A new variable based on hyperbolic sine functions is designed to prevent the unwinding phenomenon, and then a novel robust backstepping controller is developed. Initially, a nonlinear tracking law is designed to obtain the desired angular velocity and to ensure that the attitude maneuvering system could have two equilibrium points. Subsequently, an adaptive robust control law is devised, which incorporates the adaptive estimation method to update the inertial parameters in real-time. Moreover, the bounded external disturbances are taken into account in the design of the control law, and thus the robustness of the attitude control system is improved. Furthermore, the global asymptotic stability of the attitude control system is verified by the Lyapunov-Krasovskii theorem. Finally, numerical simulations are carried out to demonstrate the effectiveness and robustness of the proposed control law, as well as the anti-unwinding characteristics are perfectly validated during the attitude maneuver of rigid spacecraft. [ABSTRACT FROM AUTHOR]

Denial of services (DoS) attacks exist in wind integrated power system. DoS attacks can cause network-induced delay and packages loss in information transmission. Meanwhile, considering the parameter perturbation of controller and system model uncertainty in wind integrated power system, these may cause the system dynamic performances degradation or even instability. Based on the above considerations, the joint non-fragile automatic generation robust control of wind integrated power system under DoS attacks is studied in this paper. In order to ensure the expected system performance and more effectively utilize the limited network communication resources under DoS attacks, a novel dynamic multi-event driven mechanism based joint non-fragile H ∞ automatic generation control method is proposed. By constructing a suitable Lyapunov-Krasovskii functional and utilizing the Shur complement lemma to handle nonlinear matrix inequality, the sufficient conditions are derived to guarantee the asymptotic stability of wind integrated power system under DoS attacks. Furthermore, the performance of the proposed non-fragile regulator is demonstrated through a four-area wind integrated power system to show the feasibility and applicability. The analysis result indicates that the proposed scheme provides stronger robustness, higher wind energy utilization efficiency and more efficient communication mechanism. [Display omitted] • A multi-event driven mechanism (MEDM) based joint non-fragile control scheme is derived. • The wind-integrated power system model based on MEDM is established. • The MEDM is integrated into the joint non-fragile controller design under DoS attacks. • The MEDM based joint non-fragile H ∞ automatic generation control strategy is proposed. • It provides stronger robustness and higher wind energy utilization efficiency. [ABSTRACT FROM AUTHOR]

This paper proposes a tube-based model predictive control strategy for linear systems with bounded disturbances and input delay to ensure input-to-state stability. Firstly, the actual disturbed system is decomposed into a nominal system without disturbances and an error system. For the nominal system, solving an optimization problem, where the delayed control input is set as an optimization variable, yields a nominal control law that enables the nominal state signal to approach to zero. Then, for the error system, the Razumikhin approach is used to identify a robust control invariant set. Using the set invariance theorem, an ancillary control law is developed to confine the error state signal in the invariant set. Combining the two results, we obtain a control law that enables the state signal to remain within a robustly invariant tube. Finally, the effectiveness of the developed control strategy is validated by simulations. • An ancillary control is used to ensure the state errors stay in the invariant set. • A constraint on the delayed input is added to ensure feasibility of the algorithm. • By introducing a state error term, a novel Lyapunov function is proposed. [ABSTRACT FROM AUTHOR]

• We construct a multidimensional poverty index for chinese counties. • We establish a staggered DID model that controls for selection bias. • Highways significantly reduce county poverty. • The poverty-reduction effect of highways is conditional. • The poverty-reduction effect of highways diminishes with increasing altitude. This paper establishes a staggered difference-in-differences (DID) model to estimate the impact of highways on regional poverty using county-level panel data from China. We construct a multidimensional poverty index and use satellite-monitored night light brightness as a proxy indicator. The results demonstrate that highways significantly reduce county poverty and that the poverty reduction effect becomes increasingly pronounced over time. This result remains robust after controlling for non-random highway route selection. Furthermore, the poverty reduction effect of highways is conditional, with a significant poverty reduction effect in the less economically-developed western regions and non-municipal counties, and no significant poverty reduction effect in the economically-developed eastern and central regions and municipal districts. Moreover, the poverty reduction effect of highways gradually decreases as the average altitude of counties increases. Our tests provide empirical evidence for effective road investments in developing countries that incorporate poverty alleviation targets. [ABSTRACT FROM AUTHOR]

This paper presents a two-loop control framework for robotic manipulator systems subject to state constraints and input saturation, which effectively integrates planning and control strategies. Namely, a stability controller is designed in the inner loop to address uncertainties and nonlinearities; an optimization-based generator is constructed in the outer loop to ensure that state and input constraints are obeyed while concurrently minimizing the convergence time. Furthermore, to dramatically the computational burden, the optimization-based generator in the outer loop is switched to a direct model-based generator when the tracking errors are sufficiently small. In this way, both a high tracking accuracy and fast dynamic response are obtained for constrained robotic manipulator systems with considerably lower computational burden. The superiority and effectiveness of the proposed structure are illustrated through comparative simulations and experiments. • A general and systematic constrained control scheme for robotic manipulators. • Nonlinearities, uncertainties, state and input constraints are considered. • Adaptive robust controller is designed for high tracking accuracy. • Optimization-based generator is designed for fast dynamic response. • Experiments on Franka robotic manipulator reveal the effectiveness. [ABSTRACT FROM AUTHOR]

Synchronization of memristive neural networks (MNNs) by using network control scheme has been widely and deeply studied. However, these researches are usually restricted to traditional continuous-time control methods for synchronization of the first-order MNNs. In this paper, we study the robust exponential synchronization of inertial memristive neural networks (IMNNs) with time-varying delays and parameter disturbance via event-triggered control (ETC) scheme. First, the delayed IMNNs with parameter disturbance are changed into first-order MNNs with parameter disturbance by constructing proper variable substitutions. Next, a kind of state feedback controller is designed to the response IMNN with parameter disturbance. Based on feedback controller, some ETC methods are provided to largely decrease the update times of controller. Then, some sufficient conditions are provided to realize robust exponential synchronization of delayed IMNNs with parameter disturbance via ETC scheme. Moreover, the Zeno behavior will not happen in all ETC conditions shown in this paper. Finally, numerical simulations are given to verify the advantages of the obtained results such as anti-interference performance and good reliability. [ABSTRACT FROM AUTHOR]

This paper investigates the stabilization problem with a fixed-time approach for a flexible spacecraft subject to vibrations of flexible modes, unknown bounded disturbance, and inherent uncertainty. To estimate the modal variables of a flexible spacecraft which are often unmeasurable in practice, an observer with guaranteed fixed-time convergence is designed. Using the estimated modal variables, a fixed-time non-singular sliding mode controller is designed so that the desired attitude can be reached before a pre-specified time threshold regardless of the spacecraft's initial attitude. By incorporating the estimated modal variables in the control design, significant reduction in the steady-state error of the system response is achieved. The proposed control system is further enhanced with an adaptive law to increase robustness against unknown external disturbances and uncertainties. Stability analysis based on Lyapunov theory guarantees the convergence of observer estimation error and spacecraft attitude error to a pre-determined set before a fixed threshold. Simulation results validate the promising performance of the proposed control system, highlighting its effectiveness in achieving accurate and robust attitude control for flexible spacecraft. • A fixed-time observer with guaranteed convergence is designed. • A fixed-time non-singular sliding mode controller is developed to guide the spacecraft's attitude towards a desired target. • To further enhance the robustness of the control system, an adaptive law is integrated into the proposed controller. • The stability of the closed-loop system is rigorously analyzed using Lyapunov theory. [ABSTRACT FROM AUTHOR]

The slant-axis telescope has a novel structure, and its unique structural design is more suitable for extreme environment such as the South Pole. However, there is a lack of research on the dynamic modeling and the controller design of slant-axis telescopes at home and abroad. This paper proposes a dynamic modeling and robust control method for slant-axis telescope. Firstly, the dynamical analysis of the slant-axis telescope is carried out. The 2-degree-of-freedom rigid body model of the telescope is established by the Lagrange method. Next, combining the flexibility of the driver system and disturbance, a mathematical model of the rigid-flexible coupling system of the slant-axis telescope is completed. Then, according to the established mathematical model, a sliding mode controller based on the disturbance observer is designed to suppress the disturbance, and realize the robust control of the slant-axis telescope. Finally, the simulation results show that the disturbance observer based sliding mode controller gets better dynamic performance and anti-disturbance characteristics than the traditional Proportion-Integration-Differentiation (PID) controller in the case of considering nonlinear external interference of the model. [ABSTRACT FROM AUTHOR]

The widespread use of wheeled mobile robots (WMRs) in many fields has created new challenges. A critical issue is wheel slip, which, if not accurately determined and controlled, causes instability and deviation from the robot's path. In this paper, an intelligent approach for estimating the longitudinal and lateral slip of wheels is proposed that can effectively compensate for the negative effects of slippage. The proposed algorithm relies on three regression networks to estimate the longitudinal slip ratio of the right and left wheels and sideslip angle on terrains with different friction coefficients. The datasets collected during tests on different surfaces with various maneuvers are used to train the artificial neural networks (ANNs). A developed dynamic model of a WMR considering wheel slip and modified traction force is presented. The adaptive robust controller, based on sliding mode control (SMC), is introduced to deal with the problems related to slipping, unknown uncertainties, and disturbances. The simulation results demonstrate that the presented controller has better performance than SMC in handling external disturbances and uncertainties, which leads to reduction in tracking error and faster convergence to zero. The proposed controller with an intelligent slip estimator, has been applied to a four-wheel mobile robot to demonstrate its effectiveness and feasibility. The high accuracy of slip estimation in the mentioned intelligent algorithm has resulted in the presented method being on average 26% more effective in reducing the tracking error than the control method without slip compensation in each test for circular trajectory. • Developing a dynamic model of WMR using modified traction force. • Proposing slip estimator based on an intelligent learning for both longitudinal and lateral slip. • Eliminating the time delay in slip estimation and compensating for its effect in the same time step by predicting the slip amount. • Improved robot performance in trajectory tracking on slippery surfaces. [ABSTRACT FROM AUTHOR]

Path-tracking and lane-keeping tasks are critical to guarantee safety and navigation performance considerations for deploying autonomous cars. This paper presents a novel control framework for the path-tracking control of high-speed autonomous cars with structured uncertainties. This study introduces a nonlinear adaptive control system based on a fractional-order terminal sliding mode system while incorporating a novel Gaussian Nonsingleton type-3 fuzzy system (FOTSM-NT3FS). Therefore, the proposed controller is independent of the information about the ego vehicle's dynamic information, and instead, the dynamics are approximated through a developed NT3FLS. The developed control system exhibits robustness to measurement errors and faulty sensors, because the inputs to the NT3FS are uncertain. In order to guarantee the boundedness of the adaptation parameters, the σ − mod approach is employed. The Lyapunov stability theorem and Barbalat's lemma are used to ensure the uniform ultimate boundedness of the closed loop system and the convergence of tracking errors to the origin in finite time. High-fidelity co-simulations with CarSim and MATLAB are performed to verify the effectiveness of the proposed control scheme and are also compared to other reported methods in the literature. Based on the obtained results, the schemed controller exhibits competitive effectiveness in path-tracking tasks and strong efficiency under various road conditions, parametric uncertainties, and unknown disturbances. • Robust path tracking for uncertain-input cars, ensuring reliability despite errors. • Adaptive control with fuzzy integration for high-speed autonomy, precise maneuvering. • Stable navigation using Gaussian Nonsingleton type-3 fuzzy system, smooth tracking. • Efficient path tracking under uncertainties, outperforming existing methods. [ABSTRACT FROM AUTHOR]

This paper presents a gain-scheduling (GS) robust control strategy using the interpolation approach for ball screw drives while guaranteeing the system stability in the operating range. A set of linear-time-invariant (LTI) robust controllers is designed at selected table positions for the robustness against the uncertain load mass and the structural vibration suppression at those positions. By interpolating the LTI robust controllers, a GS robust controller is obtained to deal with the dynamic variations caused by the table motion. The closed-loop stability under the proposed GS robust controller is verified with the parameter-dependent Lyapunov function, which avoids tedious simulations to check the reliability of interpolating GS controllers before practical operations. The method presented in this paper enables the GS controller to consider the unmeasurable load mass in ball screw drives and simplifies the application complexity. The extensive experimental results demonstrate that the proposed GS robust controller significantly improves the tracking performance and the vibration suppression, in comparison to LTI controllers and GS controllers. • A gain-scheduling robust controller is developed for ball screw drives. • The table-position-dependent mode and the uncertain inertia are considered. • Parameter-dependent Lyapunov function is used to verify the closed-loop stability. • The proposed method improves the vibration suppression and trajectory tracking. [ABSTRACT FROM AUTHOR]

Navigation and proximity to non-cooperative targets have garnered the interest of both academia and industry. This paper proposes a new space operation concept that would enable two CubeSats equipped with only optical sensor to achieve autonomous and robust proximity with uncooperative satellites. This is a novel strategy for distributed spacecraft missions and applications. Because optical sensors are lightweight and therefore reduce reliance on external measurement sources, the case for their use is compelling. Designing robust guidance and control algorithm is the greatest challenge for optical sensors because relative distance information is unavailable, whereas range information is required for safe proximity. The purpose of this paper is to propose a novel concept in which two CubeSats cooperate and share angle measurement data to approach uncooperative targets despite their maneuverability. This paper introduces a new guidance scheme for proximity operations, namely cooperative augmented proportional navigation (CAPN). Modern control law is applied along line-of-sight (LOS) while classical proportional navigation is applied in the normal direction of LOS. By measuring only elevation and azimuth angles between each chaser and the target, the algorithm can account for a maneuvering target. The cooperative scheme offers estimation-based distance measurement, which enhances the observability of angle-only navigation. Target's maneuverability and different control parameter settings have been considered in simulation scenarios. The degree of observability (DOO) is then introduced as the quantitative observability analysis metric to validate the effectiveness of the guidance scheme and precision of the estimation. The results of simulations have demonstrated that the CAPN proposed in this paper is capable of completing challenging proximity missions. [ABSTRACT FROM AUTHOR]

This paper proposes a sample entropy (SampEn) based prescribed performance controller (SPPC) for the longitudinal control of a supersonic tailless aircraft subject to model uncertainty and nonlinearity. Considering that SampEn can evaluate the system's stability, a SampEn-based feedback adjust system (SFAS) is developed in this paper. With the help of SFAS, the SPPC could identify the dangerous chattering in the status signal that may lead the aircraft to lose control and make appropriate adjustments to feedback. Besides, the SPPC does not require any accurate model information and only needs to know the rough trend of dynamic functions. Although no adaptive or robust control mechanisms are introduced, the SPPC shows robustness against model uncertainty utilizing the nonlinear error feedback. Compared with traditional prescribed performance control (TPPC), the SPPC achieves better performance and safer flight. The whole control structure is developed through the backstepping technique, and the closed-loop stability is proved. At last, the advance of SPPC is verified via simulation using a high-fidelity tailless aircraft model, and the inner mechanisms of SPPC are further discussed. [ABSTRACT FROM AUTHOR]

Successive approximation techniques are effective approaches to solve the Hamilton–Jacobi–Bellman (HJB)/Hamilton–Jacobi–Isaacs (HJI) equations in nonlinear H 2 and H ∞ optimal control problems (OCPs), but residual errors in the solving process may destroy its convergence property, and related numerical methods also pose computational burden and difficulties. In this paper, the HJB/HJI partial differential equations (PDEs) for infinite-horizon nonlinear H 2 and H ∞ OCPs are handled in a unified formulation, and a sparse successive approximation method is proposed. Taking advantage of successive approximation techniques, the nonlinear HJB/HJI PDEs are transformed into sequences of easily solvable linear PDEs, to which the solutions can be computed point-wise by handling simple initial value problems. Extra constraints are also incorporated in the solving process to guarantee the convergence under residual errors. The sparse grid based collocation points and basis functions are then employed to enable efficient numerical implementation. The performance of the proposed method is also numerically demonstrated in simulations. • The proposed method handles nonlinear H 2 and H ∞ problems with a unified formulation. • Residual errors are explicitly considered in the designed numerical scheme. • The scale of the resultant quadratic programming problem only grows polynomially. [ABSTRACT FROM AUTHOR]

This paper proposes a method for high-performance motion control of the dual-valve hydraulic system subject to parameter and model uncertainties, unknown proportional valve dead-zone, and servo valve fault. By constructing a detailed dual-valve fault system model (DFSM), a disturbance observer-based adaptive robust fault-tolerant controller is proposed via the backstepping method. This controller integrates a model-based fault detection algorithm for real-time fault monitoring and subsequent controller reconfiguration. Additionally, the DFSM-based adaptive robust control (ARC) technique is applied to handle the unknown dead-zone problem and other nonlinearities, ensuring precise control. Once the servo valve fault occurs, a nonlinear observer estimates the fault and collaborates with the ARC to establish a reconfigured controller, thereby maintaining motion control. The effectiveness of the proposed method has been experimentally verified. • The novel fault-tolerant control algorithm for dual-valve hydraulic system is investigated. • The novel dual-valve faults system model is proposed. • The model-based fault detection algorithm and nonlinear disturbance observer are established. • The advanced adaptive robust fault-tolerant controller is designed. [ABSTRACT FROM AUTHOR]

Mechanical systems subject to constraints play a essential role in the field of control engineering, profoundly influencing the design and performance of control strategies. Consequently, there is a compelling need to explore diverse control methods to effectively tackle the complex task of stabilizing nonlinear systems while ensuring the constraints are not violated. In this context, this paper proposes a design procedure for position-constrained controllers in robot manipulators. The solution relies on the construction of a diffeomorphism (a differentiable coordinate transformation) that maps all the trajectories of the constrained dynamics into an unconstrained one. The controller design is carried out in the unconstrained dynamics without dealing directly with the constraints. The proposed family of controllers employ an explicit control law which circumvents the need for additional time-consuming computation for feasibility and/or optimization. Moreover, the proposed controller is parametrized by a class of diffeomorphisms which can be selected by the designer. Exponential stability in constrained and unconstrained position states is achieved, in the certain case. For the uncertain case, the controller is augmented through sliding modes guaranteeing finite-time convergence towards the manifold and keeping the exponential convergence within the manifold dynamics. The approach is validated through experiments in an actual 2 DOF lightweight robot manipulator. • A diffeomorphism-based control law for MIMO constrained nonlinear systems. • The explicit controller ensures (local) exponential convergence of the all states. • A robustification of the controller to deal with uncertainties via sliding modes. [ABSTRACT FROM AUTHOR]

In this paper, a delayed distributed proportional control is developed for a class of multiple-input-multiple-output systems in order to reduce the effects of external disturbances and uncertain dynamics. The system under consideration is a three degrees-of-freedom planar robot, consisting of an active joint driving the first link and passive flexible joints for the second and third links. The control challenge for this system is to drive the flexible arm around the desired setpoint or trajectory by controlling the first link. Actually, by using a specific Lyapunov-Krasovskii storage functional associated with a constrained optimization problem, the robustness of the proposed proportional retarded control action is achieved. This analysis, together with the attractive ellipsoid concept allows to conclude with Ultimately-Uniformly-Bounded stability. The closed-loop control algorithm is tested in numerical simulation and a comparative study with some existing recent control schemes based on the performance error is presented. • The proposed control scheme belongs to a class of multivariable proportional time delay distributed controller. • After finite time the trajectories of a flexible manipulator stay within reduced size attractive ellipsoid. • Ultimate Uniformly Bounded Stability of the controlled system is demonstrated by using a Lyapunov-Krasovskii functional. • The proposed algorithm can also be adapted for a class of nonlinear uncertain/disturbed multivariable output systems. • A sufficient condition to guarantee the feasibility of specific Bilinear Matrix Inequality is presented. [ABSTRACT FROM AUTHOR]

This paper proposes a fixed-time tracking control for robot manipulators in the presence of parametric uncertainties and disturbances. An auxiliary function is first proposed for constructing a fixed-time sliding manifold. Benefited from this fixed-time sliding manifold, a singularity-free robust control is proposed to evade the effects of algebraic loop problem of the commonly-used sliding mode controls (SMC). The key advantages of the proposed approach are: (i) exact fixed-time stability featuring the convergence time does not relate to the initial conditions and is acquired in advance; (ii) the singularity and algebraic loop problems are eliminated completely; (iii) a simple and intuitive control structure is used for easy implementation of trajectory tracking control for uncertain robot manipulators with faster transient and higher steady-state precision. Simulations and experimental comparisons validate the improved tracking performance of the proposed approach. • Propose a non-singular terminal sliding mode control with fixed-time convergence. • Prove exact fixed-time tracking stability. • Features include exact fixed-time stability with simple structure. • Demonstrate the improved performance. [ABSTRACT FROM AUTHOR]

Due to the underactuated and unstable nature, the control of unmanned bicycle robots is a challenge. The presence of unknown and time-varying uncertainties in the system adds to the difficulty of control for the unmanned bicycle robot. From the perspective of constraint-following, this paper proposes a new control approach to address uncertainties in the unmanned bicycle robot system. The uncertainties of the unmanned bicycle robot system are constrained within certain limits, but the bounds are unknown, which can pose a challenge for designing a control approach. Through the implementation of a leakage-type adaptive law that modifies the control system in accordance with tracking errors, the potential exists to confine the boundaries of uncertainties. The performance of uniform boundedness and uniform ultimate boundedness is shown by the Lyapunov stability theory. Numerical simulation of a representative case is performed to illustrate the effectiveness of the proposed control. • A controlled system is studied to follow a set of prescribed constraints. • Uncertainties are described as degree information based on fuzzy set theory. • An adaptive robust control is designed based on constraint-following. • Uniform boundedness and uniform ultimate boundedness can be guaranteed. • The proposed control is demonstrated by unmanned bicycle robot. [ABSTRACT FROM AUTHOR]

The design of robust state- and output-feedback control for uncertain discrete-time systems with physical magnitude and rate constraints on their actuator dynamics was addressed. Unlike the traditional methods such as anti-windup (AW) methods, nested ellipsoids, model predictive controllers (MPCs) and integral quadratic constraints(IQCs) formulated by sector bounded inequalities, this paper uses a transformation of the system dynamics to a form which considers control signal and its rate as controlled outputs and using discrete-time ℓ ∞ induced (peak-to-peak) norm from disturbance inputs to these outputs. To cope with the magnitude and rate bound non-linearities together, the induced ℓ ∞ norm from disturbance input to the outputs involving control signal and its rate is utilised. On the other hand, discrete-time(DT) induced ℓ 2 norm from disturbance input to the main controlled output is used to mitigate the effects of disturbances. We can tackle this ambitious non-linear control problem in the domain of linear convex multi-objective optimal control problem, which can be solved by effective semi-definite optimisation methods by using the proposed transformation and handling the control constraints in terms of worst case peak-to-peak gain of the system. Extended Linear Matrix Inequalities (LMIs) and full block S-procedure based design conditions developed over Linear Fractional Representation(LFR) framework allow the user to obtain robust state- and output-feedback control solutions with reduced conservatism. For the first time, this paper introduces an extended LMI based robust output-feedback control design for magnitude and rate bounded (MRB) systems, using full block S-procedure. We demonstrate the performance of the proposed controller through several simulations over benchmark examples covering systems having multi-variable structures and uncertainties. Our study also involves comparison results with a recently introduced technique based on multi-stage AW technique. The simulation results show that the proposed method of this paper is much effective and less conservative compared to the recent AW method provided in the literature. • A robust dynamic-output feedback controller is provided for systems with constraints. • Multi-objective topology is used with acceleration form representation of the process. • To deal with uncertainties, full block S-procedure is adapted to the design. • The method provides an alternative to recently developed anti windup techniques. [ABSTRACT FROM AUTHOR]

Modern space missions for Earth Observation (EO) purposes often rely on satellites equipped with very large flexible appendages, such as antennas and solar panels, which are demanded to perform agile slew manoeuvres. In most cases, the elasticity of such systems cannot be neglected in the design of the attitude controller, as excessive elastic displacements of the structural elements may compromise their stability and pointing performance. In this scenario, this paper aims at proposing an automated nested optimization framework to simultaneously optimize spacecraft structural and control dynamics, to be applicable to a wide range of flexible spacecraft. The objective of such a co-design architecture is to modify design parameters, at both structural and control levels, to minimize the mass of the spacecraft while maximizing its agility and satisfying imposed requirements. Moreover, as robust multivariable techniques have become more and more applied to ensure satisfactory robust performance margins, this paper's goal is to pose a multi-channel structured H ∞ control architecture in the co-design problem. To guarantee the generality of implementation, a structural design tool (MSC Nastran) is interfaced with a coding environment (Matlab/Simulink) to set-up an autonomous exchange of information between structural and control domains. Starting from an initial definition of the spacecraft material, geometry and control requirements (in terms of loop-shaping transfer functions), relevant parameters are extracted from the structural tool and a linearized dynamic model assembled. Then, a controller is synthetized based on the provided requirements, followed by a verification on the nonlinear plant of the satellite. The procedure is repeated until the stop criteria (based on tolerance and max iterations) is satisfied. Finally, the output of the proposed architecture is obtained as an optimized structural model and robust controller tailored for the satellite dynamics. • The problem of structural/control co-design of flexible spacecraft is addressed. • A general framework interfacing a commercial finite element code and a coding environment is proposed. • The architecture is posed as a nested robust optimization. • A case study composed of a satellite with two flexible solar panels is proposed. • The framework is tested on the satellite non linear model. [ABSTRACT FROM AUTHOR]

To handle the tracking control problem of the magnetic wheeled mobile robot (MWMR), this paper developed an online robust tracking control scheme by adaptive dynamic programming (ADP). The problem, that how to achieve optimal tracking control of continuous-time (CT) MWMR system with the time-varying unknown uncertainty, can be solved indirectly through matching the optimal tracking control of the associated nominal system. A single critic NN-based actor-critic structure is tailored for simpler controller architecture. By minimizing the Bellman error with gradient descending and least-squares updating laws, the critic NN weights can be optimized online. Thus the optimal cost function and the optimal control signal can be approximated with high precision. Using the Lyapunov stability theorem, the convergence of the critic NN weights, and the stability of the closed-loop system is provided. Simulations, in comparison with robust PD control and adaptive control, are presented to illustrate the effectiveness of the proposed tracking control method for the MWMR. • For the magnetic wheeled mobile robot, a robust tracking control scheme based on ADP is developed in this paper. • With single critic NN based ADP and the filter tracking error-based control system state variable simplifies the control structure. • The equivalence of robust tracking control and optimal tracking control is analyzed. [ABSTRACT FROM AUTHOR]

• Hybrid microgrid is an emerging and exciting research field in power engineering. • Presents systematic review on various control strategies for hybrid microgrid. • Comparison between control strategies satisfying various control objectives. • Discussion on research challenges in use of effective and robust control scheme. • Discussion on emerging trends in hybrid microgrid's operation and control. Presently, there is huge development in conventional power systems due to the evolution of modern smart grids, wherein interconnected microgrids with a high level of energy storage and renewable energy penetration are gaining popularity in the modern distribution network. Future electrical distribution systems, or even transmission structures that combine AC and DC sources and loads are thought to be most promising when it comes to hybrid AC-DC systems. Using a combined operation of both AC and DC microgrids through an interfacing converter, hybrid AC-DC microgrids are advanced and benefitted with the use of both AC and DC topologies. Power management techniques for these microgrids are among the most important operational aspects. This paper provides a systematic review on numerous schemes to control hybrid AC-DC microgrids. Basically, microgrid control strategies are categorized as local control and coordinated control. Coordinated control is further divided in three control strategies as, distributed, centralized, and decentralized control. All these control strategies are employed to satisfy many control objectives, like bus voltage and frequency regulation, power sharing, and management, power quality, stability and reliability improvement, energy management, and economic dispatch. In this paper, various aspects associated with these control objectives and limitations in their control strategies are discussed. Also, future prospects on control of hybrid AC-DC microgrids and an effective and robust control strategy for power management possibly to be employed, are presented in the concluding section of this paper. [ABSTRACT FROM AUTHOR]

In this paper, cooperative robotic manipulators under uncertain base coordinate are investigated. The coordinate uncertainties result in biases of cooperative robotic dynamics, which involve horizontal and vertical translational errors in the task space and rotational errors in the joint space. To the best of our knowledge, uncertainties in the base coordinate system of cooperative robotic manipulators have drawn little attention in existing literature. To solve this problem, this paper presents an adaptive robust controller for the synchronized control of two cooperative robotic manipulators. An adaptive neural network associated with base coordinate parameter adaption law is proposed to estimate the cooperative system parameters given unknown system dynamics and base coordinate uncertainties. A synchronization-factor-based robust slide mode controller is then derived to stabilize the target position and internal force between the cooperative manipulators. Mathematical proof and numerical experiments under various conditions are conducted. The results demonstrate the satisfactory and effective convergences of both the cooperative robotic trajectory and internal force despite of uncertainties in the base coordinate system. • The base uncertainties including both translation and rotation errors are modelled. • A base coordinate parameter adaption law is proposed. • Adaptive neural network is proposed to estimate cooperative system uncertainties. • A virtual synchronization-factor-based robust sliding controller is presented. • Position and internal force tracking errors quickly converge to zero in four cases. [ABSTRACT FROM AUTHOR]

This paper aims to tackle the three-dimensional trajectory tracking problems of small fixed-wing unmanned aerial vehicles subject to nonlinearities, uncertainties and wind disturbances via adaptive techniques. The control objective is to efficiently control the thrust and the deflections of control surfaces to ensure the unmanned aerial vehicle arrives at a specified location within a given time frame. However, achieving this goal for small fixed-wing unmanned aerial vehicles can be challenging because the precise dynamic model and several parameters are not accessible, making most existing control strategies unworkable. Motivated by these facts, based on feedback linearization techniques, we derive linear models with equivalent disturbances to describe the translational dynamics without requiring precise aerodynamic force model information. To deal with the dilemmas where the norm bounds of equivalent disturbances depend on control inputs, system states, and unknown disturbances, a novel robust adaptive control strategy is designed for position control. Based on the assumption of two-time separation, the control scheme incorporates two parts, namely, a position controller containing the horizontal-plane and altitude parts and a robust filter-based attitude regulator. Also, to prevent chattering issues, we design a practical and robust adaptive position controller under which the tracking error is ultimately bounded The overall closed-loop stability is theoretically investigated based on the Lyapunov arguments. Hardware-in-loop simulation experiments are performed to testify our developed control scheme. • A novel robust adaptive control strategy is proposed to deal with the uncertainties related to not only system states but also to control inputs. • A cascade control strategy is employed to solve the trajectory tracking problems of fixed-wing UAVs. • A robust adaptive three-dimensional trajectory tracking controller is designed. • Hardware-in-Loop simulations are conducted. [ABSTRACT FROM AUTHOR]

This paper addresses the regulation of water quality influencers such as Organic Nitrogen, Ammonia Nitrogen, Nitrate Nitrogen, Dissolved Organic Carbon and Dissolved Oxygen for a sub-surface flow horizontal wetland in a controlled environment. The plant uncertainty is quantified by using measurement data. The robust control of the process is achieved using a decentralized quantitative feedback theory based control strategy. The control structure also employs a feed-forward mechanism to minimize loop interactions and feedback control to ensure stability, tracking and disturbance rejection. The numerical simulations and hardware-in-loop implementation show that the performance specifications are robustly met. • The control of water quality deciding variables by using a constructed wetland • The parametric uncertainty is quantified using measurement data collected • A decentralized quantitative feedback theory based robust controller is adopted • Each loop is equipped with feed-forward controllers to minimize coupling effects • Performance is verified by numerical simulation and hardware-in-Loop validation [ABSTRACT FROM AUTHOR]

This paper addresses the control problems of distributed attitude coordination for multiple flexible spacecraft based on the feedback of inertial vector measurements. It is assumed that the angular velocity information is not available, and the modal variable cannot be measured. The orientation error model with vector measurements is introduced. And then the distributed attitude synchronization control scheme is presented without actuator faults or disturbances. It is guaranteed that the desired equilibrium is locally asymptotically stable and the undesired equilibrium is unstable. Meanwhile, the domain of attraction is given by inequality constraints. In the case that there exist actuator faults and external disturbances, a robust fault-tolerant control strategy is developed to realize attitude synchronization. The hyperbolic tangent function in place of sign function is adopted to eliminate external disturbances. Meanwhile, the adaptive laws are proposed to estimate actuator faults. The salient feature of these control approaches is that no modal variable observers are utilized and the control schemes are robust to the inertia uncertainty of spacecraft. Finally, numerical simulations are implemented to manifest the validity of the presented control schemes. [ABSTRACT FROM AUTHOR]

The fuel cell airpath multivariable control problem of optimally coordinating the electric compressor motor and the back-pressure valve to achieve efficient and safe conditions, for both steady state and transient operation, has not been completely addressed in the literature. This paper proposes a nonlinear model predictive control strategy, implemented via the Garrett Motion proprietary NMPC toolbox, to regulate the oxygen stoichiometry and the cathode pressure of an automotive fuel cell airpath system, while avoiding compressor surge and air starvation. The controller set-points are optimized, using the nonlinear model, to achieve the maximum system power as a function of the operating stack condition. The effectiveness and robustness of the proposed control strategy have been validated by means of a simulated World harmonized Light-duty vehicles Test Cycle (WLTC), under both state feedback and model parameters uncertainties. [Display omitted] • MPC ensures compressor surge and oxygen starvation avoidance under severe dynamic scenarios. • Controller robustness assessed via a WLTC regulatory cycle under noisy and uncertain conditions. • Fuel efficiency is not significantly sensitive with respect to different controller calibrations. [ABSTRACT FROM AUTHOR]

It is well known that induction motors consume active and reactive energy from the utility grid to operate; additionally, when a power converter drives the motor, a high content of current harmonics is produced, and both circumstances decrease the utility grid power factor, which later requires to be improved. To this end, this paper presents a novel complete solution through a robust control system employed in a back-to-back topology power converter to deliver, instead of consuming, regulated reactive power toward the main grid, which comes from a capacitor bank in a DC-bus. This salient feature of delivering reactive power, and simultaneously, regulating the speed for an induction motor, becomes one of the contributions of this work to enhance the power factor. The robust converter controller is synthesized in a cascade form, by applying the linearization block control and state-feedback techniques. These techniques are combined with the super-twisting strategy for canceling the nonlinearities and the effect of the external disturbances. The complete system consists of a back-to-back converter, an LCL filter coupled to the main grid for mitigating the current harmonic content, and an induction motor under variable load conditions. Experimental tests expose the performance and robustness of the proposed controller, where a robust control for the reactive power acts under sudden changes in the active power produced through abrupt variations in the motor load. [Display omitted] • To deliver regulated reactive power for power factor enhancement in the utility grid. • Simultaneously, regulating the induction motor speed through a robust control system. • To present experimental results for validating the proposed cascade control system. [ABSTRACT FROM AUTHOR]

In this paper, an iterative neural network adaptive robust control (INNARC) strategy is proposed for the maglev planar motor (MLPM) to achieve good tracking performance and uncertainty compensation. The INNARC scheme consists of adaptive robust control (ARC) term and iterative neural network (INN) compensator in a parallel structure. The ARC term founded on the system model realizes the parametric adaptation and promises the closed-loop stability. The INN compensator based on the radial basis function (RBF) neural network is employed to handle the uncertainties resulted from the unmodeled non-linear dynamics in the MLPM. Additionally, the iterative learning update laws are introduced to tune the network parameters and weights of the INN compensator simultaneously, so the approximation accuracy is improved along the system repetition. The stability of the INNARC method is proved via the Lyapunov theory, and the experiments are conducted on an home-made MLPM. The results consistently demonstrate that the INNARC strategy possesses the satisfactory tracking performance and uncertainty compensation, and the proposed INNARC is an effective and systematic intelligent control method for MLPM. • A iterative neural network scheme with network parameters and weights tuned via iterative learning is proposed to improve the uncertainty approximation capability. • The proposed scheme integrating of model-based and data-based method improves the tracking performance of the maglev planar motor. • The stability of maglev planar motor regulated by the proposed iterative neural network adaptive robust control method is proved via Lyapunov theory. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptive fractional-order nonsingular terminal sliding mode (AFNTSMC) control scheme combined with the independent joint control approach for trajectory tracking of three-axis gimbal platforms (GPs) mounted on a moving vehicle subjected to external disturbances. To achieve accurate images taken by the camera mounted on the GP, the motions and vibrations of the vehicle must be isolated from the camera. Thus, precise mathematical modeling of a three-axis GP with considering the external disturbances is studied, such that the GP tracks the target accurately and holds the line of sight stationary. Various tests with different vehicle conditions are performed to collect the movement data to be considered as the desired input for the GP. Thanks to the utilization of AFNTSMC, fast convergence together with simultaneous accurate trajectory tracking and strong robustness can be ensured. Corresponding comparative simulation results validate the effectiveness of the theoretical design results and superiorities of the proposed method over the existing methods. • This paper presents the precise modeling of a three-axis gimbal platform (GP) with considering the external disturbances. • An adaptive fractional-order nonsingular terminal sliding mode control scheme is proposed to deal with the control problem of GP with real input data in the presence of external disturbances. • The chattering phenomenon is alleviated without deteriorating the robustness of the system. • Comparison results demonstrate the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

The paper develops a methodology for the design of coherent equalizing filters for quantum communication channels. Given a linear quantum system model of a quantum communication channel, the aim is to obtain another quantum system which, when coupled with the original system, mitigates degrading effects of the environment. The main result of the paper is a systematic equalizer synthesis algorithm which relies on methods of state–space robust control design via semidefinite programming. [ABSTRACT FROM AUTHOR]

The development of a sampled-data robust controller, applied to a 2-DoF helicopter system, is proposed in this paper. The helicopter presents a nonlinear dynamics, which is modeled in this paper using a quasi-LPV approach, thus allowing the application of convex LMI conditions for the determination of the desired controllers. The robustness against effects such as sampling rate variation, noise and modeling approximations is assured mainly through a guaranteed bound for the L 2 norm. Also, a performance index based on the H 2 concept is used for the synthesis procedure, which is one of the main contributions of this paper. An algorithm is proposed to optimize the performance while guaranteeing the desired robustness. The analysis and validation of the proposed synthesis procedure are performed both through computational simulations and by applying the controllers on a physical 2-DoF helicopter, which could be satisfactorily stabilized. [ABSTRACT FROM AUTHOR]

This paper presents a new method that uses the equivalent-input-disturbance (EID) approach to estimate the wind load of a seismically isolated building. To verify the control performance of wind-resistant design methods and devices, wind-load data are important for structural design of skyscrapers. However, wind loads cannot be measured directly and is usually estimated based on structural responses. Previous studies focused on a building model in which the damping coefficient is proportional to a linear combination of mass and stiffness (referred to as Rayleigh damping). These existing methods cannot be directly applied to a seismically isolated building because its damping is not Rayleigh damping. Moreover, a structural model usually contains uncertainties caused by modeling errors that cause the degradation of estimation performance. To solve these problems, this paper combines the EID approach with a robust control strategy to design a wind-load estimator for a seismically isolated building with uncertainties. First, the configuration of an EID-based estimation system is shown. Next, a robust wind-load estimator is presented. Then, simulations are carried out to demonstrate the validity of the presented method using wind-load data obtained from a wind-tunnel test. An 11-degree-of-freedom model of a seismically isolated building is used for numerical verification. The results show that, even if a model contains 20% uncertainties, the presented method accurately estimates the wind load of a seismically isolated building. [ABSTRACT FROM AUTHOR]

This paper concentrates on the performance recovery-based fuzzy robust control of networked nonlinear systems via a deferred actuator-switching approach. The main design procedure of this paper is divided into three parts: 1) nominal controller design; 2) monitoring function and shifting function design; 3) reconfigurable controller design. With the aid of low-computation method and fuzzy logic systems, a structurally and computationally efficient nominal controller is designed for fault-free. Then, an actuator-switching rule is established based on monitoring the stabilization error. Furthermore, a new error transformation is constructed via designing the shifting function, by which tangent barrier Lyapunov functions are effective at the replacement instant. Finally, the stabilization error recovers into the prescribed performance within a specified period of time, and a reconfigurable controller is designed for the backup actuator. By employing the event-triggering mechanism with the relative threshold strategy, communication loads from controllers to actuators are reduced. Simulation examples are given to confirm the effectiveness of the proposed control approach. [ABSTRACT FROM AUTHOR]

In the last couple of decades, the integration of photovoltaic (PV) systems with the utility grid has gained significant attention due to its potential to harness renewable energy and contribute to sustainable power generation. However, the integration of the PV system into the grid leads to issues related to power quality and system stability under varying solar irradiation, dc offset, and distorted grid conditions. Therefore, this paper focus on the robust and efficient control of a single-phase, two-stage PV grid-tied system to improve power quality and stable system operation under abnormal grid conditions. These objectives can be achieved using the synchronization method, dc link voltage control, and grid current control. The hybrid PLL is proposed in this paper for synchronization and to mitigate the effect of dc offset and lower-order harmonics in the estimated phase and frequency. Further, the sliding mode voltage controller and integral sliding mode current controller are proposed for dc link voltage regulation and grid current tracking. The stability of voltage and current control loops is analyzed using the Lyapunov stability theory. Furthermore, the proposed schemes are validated using MATLAB simulation and experimental analysis. The proposed approach outperforms conventional methods and exhibits better disturbance rejection capability under both dynamic and steady-state conditions, making it a robust and efficient control strategy for grid-tied systems. [ABSTRACT FROM AUTHOR]

• This paper introduces an advanced H∞ frequency control method for MGs, addressing uncertainties in secondary frequency control resources. By integrating parametric cyber uncertainties, it effectively counteracts unknown cyber-attack impacts, ensuring stable dynamic performance during cyber-attacks without requiring additional isolation or detection methods, simplifying MG control. • This study assesses cyber threats, incorporating physical uncertainties and RES/load fluctuations. It models key cyber threats (FDI, DoS, controller hijacking) and designs robust controls treating cyber-attacks and RES/load fluctuations as bounded uncertainties and disturbances. • The proposed H∞ control surpasses classical H∞ , optimal PI, and traditional frequency control in enhancing MG security, control, and functionality. It enables proactive control across diverse scenarios, ensuring cyber robustness, resilience, and uninterrupted performance against potential disruptions. • The application of the proposed robust control can be extended to the interconnected MG operations, significantly improving overall robust performance, even when the robust control is implemented in just one area during multiple cyber-attack events. A microgrid (MG) is a smart grid cyber-physical system, with component coordination relying on cyber resilience. Weak communications, protocols, and tools make the MG's secondary frequency control vulnerable to various cyber-attacks, posing new challenges and stability risks. In response to this challenge, this paper introduces the enhanced robust H ∞ technique considering the dynamic impacts of cyber-attacks on secondary frequency control to develop a secondary frequency control loop, improving the regulation performance and cyber resiliency of the MG frequency. The secondary control cyber-attack strategies mainly rely on false data injection (FDI), denial of service (DoS), and controller hijacking. These attack techniques are simultaneously considered in formulating the H∞ problem and control synthesis as unstructured parametric uncertainty, attenuating the concurrent cyber impacts. The study extends a load frequency control model to illustrate how cyber-attacks can be represented mathematically and physically in the MG. The results reveal that cyber-attacks affect secondary frequency control elements differently depending on the type of cyber threats used. By implementing an enhanced H∞ controller, the MG can effectively maintain stable frequency levels even when faced with malicious attacks and disruptions caused by renewable energy sources and loads. [ABSTRACT FROM AUTHOR]

Improving the level of innovation factor allocation is an important route to achieve high-quality economic development in China and has received much attention from scholars. As a policy system to change the old and new dynamics of innovation, the impact of innovation pilot cities on the allocation of innovation factors is of great importance. Using a sample of 254 prefecture-level cities in China from 2006 to 2019, this paper empirically analyses the impact of innovative pilot city policies on the allocation of innovation factors and their paths of action using a multi-temporal double-difference model. The study finds that the innovative pilot city policy significantly improved the level of innovation factor allocation, and this result held true after considering a series of robustness tests and endogeneity tests. Mechanistic tests show that the innovation pilot city policy has an impact on the allocation of innovation factors through the factor mobility effect and the innovation environment effect. Heterogeneity test shows that the influence of innovation pilot city policies on innovation factor allocation is greater in cities with higher administrative levels and better geographical locations. The economic consequences show that the innovation pilot city policy can significantly promote high-quality regional economic development. This study provides useful lessons for giving full play to the innovation-driven policy's innovation factor allocation effect, thereby enhancing China's high-quality economic development. • This paper studies the influence of innovative pilot cities on the allocation of innovation factors. • It provides a new method for measuring innovation factor allocation. • The basic results were confirmed by a series of robustness tests and endogeneity tests. [ABSTRACT FROM AUTHOR]

Direct Torque Control (DTC) scheme introduces a robust and simple control of electrical drive. However, its shortcomings such as broad torque ripple and variable switching frequency have offered several improvements like Space Vector Modulation (SVM) strategy, multilevel inverter (MLI) topology, etc. The conventional DTC which is fed by the two-level inverter has limited voltage vector, results in some difficulties to optimize the operation, especially at low operating speed. In contrast to MLI, the abundant of voltage vector has provided various amplitudes and angles that can overcome the problem of conventional DTC. Thus, this paper introduces the selected optimal voltage vector obtained from five-level Cascaded H-Bridge (CHB) inverter that employs in DTC hysteresis-based to achieve better optimization that similar to the DTC-SVM. Initially, the research work begins with an investigation on the performance comparison between a DTC hysteresis-based between two-level inverter (conventional method) and a five-level CHB inverter (proposed method). Here, a DC generator acted as a load is employed to control the operating speed instead of the speed controller (speed controller is negligible). Hence, the DTC method is optimized by minimizing the torque ripple as well as retaining the torque control capability at constant torque region on several operating speed. The selected optimal vector from the look-up table DTC of five-level CHB inverter must be dynamically appropriate to any change of torque (increased or decreased torque). For simplicity, this paper will only discuss the experimental results for both topologies of drive system. From the experimental results, it is verified that the torque ripples by the proposed method have achieved 10% and 50% reduction at high and low operating speed respectively. It is found that the DTC hysteresis-based result simpler control method than DTC-SVM while maintaining similar output performance. • Five-level Cascaded H-Bridge (CHB) inverter is proposed in the DTC scheme. • Optimal voltage vector is selected to analyze the torque performance on the several operating speeds. • The torque performance on each operating speed is verified by using experimental test. [ABSTRACT FROM AUTHOR]

This paper deals with an application of robust state feedback pole placement for discrete-time polytopic systems with stochastic disturbance attenuation. A set of stochastic signals is described using differential entropy functional. In the paper the parameter-independent robust state-feedback controller design procedure for linear discrete-time polytopic systems with theoretic-information constraints on the set of external random disturbances is proposed. Such additional constraints allow to find a tradeoff between H 2 and H ∞ control with better control energy consumption and improved robustness against random disturbances. This approach is applied to PWM inverters with LCL filters connected to the grid under uncertain parameters. Simulation results indicates that proposed controller allows to improve frequency and transient responses with better performance than existing ones. [ABSTRACT FROM AUTHOR]

Minimizing the amount of fuel consumed by a moving vehicle can be formulated as an optimal control problem that determines the speed profile that the vehicle should follow. The fuel consumption is generally a function of speed and acceleration, and is optimized under external parameters (e.g., road grade or surrounding traffic conditions) known to affect fuel economy. Uncertainty in the traffic conditions, and in particular traffic speed, has seldom been investigated in this context, which may prevent the vehicle from following the optimal speed profile and consequently affect the fuel economy and the journey time. This paper describes two stochastic optimal speed control models for minimizing the fuel consumption of a vehicle traveling over a given stretch of road under a given time limit, where the maximum speed that can be achieved by the vehicle over the journey is assumed to be random and follow a certain probability distribution. The models include chance constraints that either (i) limit the probability that the desired vehicle speed exceeds the traffic speed, or (ii) bound the probability that the journey time limit is violated. The models are then extended into distributionally robust formulations to capture any uncertainties in the probability distribution of the traffic speed. Computational results are presented on the performance of the proposed models and to numerically assess the impact of traffic speed variability and journey duration on the desired speed trajectories: The results affirm that uncertainty in traffic speeds can significantly increase the amount of fuel consumption and the journey time of the speed profiles created by deterministic model. Such increase in journey duration can be mitigated by incorporating the stochasticity at the planning stage using the models described in this paper, and more so with the distributionally robust formulations particularly with higher levels of uncertainty. The solutions themselves generally exhibit low levels of speeds, which ensure the feasibility of the speed profile against any variabilities in the traffic speed. • Traffic speed uncertainty can increase fuel consumption and journey duration. • Stochastic optimal control helps to mitigate the impact of traffic speed uncertainty. • Distributionally robust optimal control can be used for larger uncertainties. • Stochastic optimal control models can be expressed as mixed integer programs. • Planned speeds tend to be lower to provide robustness against variability. [ABSTRACT FROM AUTHOR]