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Reluctance actuators (RA) are a type of electromagnetic actuator that offers high forces for short-range motions. The RA takes advantage of the electromagnetic reluctance force property in air gaps between the stator core and mover parts. The stator generates a magnetic flux that produces a magnetic attraction force between the stator and the mover, where the output force is dependent on the air gap displacement nonlinearly. It is demonstrated that the RA can produce a force that is effective and suitable for millimeter-range high-acceleration applications. One application for the RA is the short-stroke stage of photolithography or lithography machines, for example. The RA is available in a wide variety of configurations, such as C-Core, E-Core, Maxwell, and Plunger-type designs. The RA requires precise dynamic models and control algorithms to help linearize the RA for better control and optimization. Some nonlinear dynamics include magnetic hysteresis, flux fringing, and eddy currents. The RA is shown to have a larger force density than any other traditional actuator designs, with the main disadvantage being the nonlinear and hysteresis nonlinearities, making it difficult to control precision motion applications without proper dynamic and control models in place. This review documents currently available knowledge of the RA such as available applications, configurations, dynamic models, measurement systems, and control systems for the RA. • Provides a consolidated overview of available applications, configurations, dynamic models, measurement systems, and control methodologies for RAs. • Explores the unique electromagnetic properties of RAs for high-force, short- range motions. • Discusses various RA configurations and their suitability for different applications. • Addresses challenges posed by nonlinearities such as magnetic hysteresis, flux fringing, and eddy currents. • Emphasizes the importance of precise dynamic models and control algorithms for linearizing and optimizing RA performance. [ABSTRACT FROM AUTHOR]

A drag sail is a propellantless device suitable for passive deorbiting of satellites after their end-of-life. It exploits atmospheric drag to gradually reduce the kinetic energy of the decommissioned satellite and cause it to lose altitude over time. It is well known that the braking effect of the atmosphere is greater the surface exposed to the flow of the atmospheric particles relative to the satellite. For this reason, a drag sail is essentially a large and lightweight membrane, which is deployed by the satellite when it is to begin orbital decay. For given environmental/initial conditions and inertial characteristics of the deployed system, the braking effect of a drag sail is more intense if its perpendicular axis is constantly aligned with the direction of the relative particle flow. For this purpose, a sliding mode control strategy is adopted. The reference to follow is obtained by propagating the spacecraft orbital dynamics along with its attitude dynamics. Various orbital perturbations and the disturbance torque due to atmospheric drag are implemented in the numerical code to verify the robustness of the proposed control law. It is also assumed that the spacecraft control torque vector is bounded in magnitude and always belongs to the plane of the braking device. The results show that the proposed strategy is effective in accurately tracking the reference attitude and that it is robust, being able to track a reference that varies unpredictably due to both orbital and attitude perturbations. • The paper analyzes the active attitude control problem of a drag sail. • The reference to follow is obtained by propagating the perturbed orbital dynamics. • A sliding mode control law is proposed to perform the attitude adjustments. • The control law is designed by imposing a limit on the magnitude of the input signal. • Numerical simulations indicate the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

In this paper, a quick convergence adaptive structure is proposed for trajectory tracking of an articulated type robotic manipulator using the Hardware in the Loop (HIL) simulation technique. A novel Nonlinear Quick Convergence Adaptive Sliding Backstepping Control (QCASBC) algorithm is implemented on a C2000 real-time controller board. The performance of the proposed control algorithm is inspected concerning the sliding mode PID (SM-PID) control technique to estimate its correlation with the proposed algorithm. The experimental part of the HIL simulation tests has been carried out on a simulated model of a three-link serial robot manipulator. A dynamic model of the robotic manipulator has been developed using Matlab Simulink software and its performance is analyzed using the HIL technique via a C2000 real-time controller for tracking the desired trajectory. Results show that the speed of convergence while tracking the desired trajectory of the manipulator is better in the proposed algorithm. It is also estimated that the positional error of the QCASBC algorithm is superior to the SM-PID control algorithm. The observed average angle error is improved by 14% and the average response time error is improved by 11% by using the proposed QCASBC algorithm compared to the SM-PID approach. [ABSTRACT FROM AUTHOR]

This paper introduces a novel approach for regulating the pose of a free-flying dual-arm anthropomorphic space manipulator system (SMS) using a finite-time state-dependent Riccati equation (SDRE) controller. The proposed system finds applications in on-orbit satellite inspection, servicing, space structure assembly, and debris manipulation. The dual-arm SMS presented in this work consists of two 7 degrees of freedom (DoF) robotic arms mounted on a free-flying spacecraft, resulting in a complex 20-DoF system. Due to the high number of DoFs, advanced controller design and efficient computations are necessary. The finite-time SDRE controller relies on the state-dependent coefficient (SDC) parameterization matrices, which are nonlinear apparent linearizations of the dynamics. Conventionally, the computation of SDC matrices is offline and relies on the a priori derivation of the analytical equations governing the dynamics of the system. However, this strategy becomes computationally impractical for high DoF plants. To overcome this issue and deliver a more viable solution, a numerical method to construct and update the SDC matrices at each time step is presented. This approach relies on a screw-theory-based recursive Newton–Euler algorithm designed to reconstruct the manipulator inertia and Coriolis matrices. These quantities are the building blocks of the SDC parameters used in the synthesis of the SDRE controller. Simulation results demonstrate the performances of the finite-time SDRE controller augmented with the online update of the state-dependent coefficients. • Automatic derivation of the dynamics of free-flying robot with multiple open chains. • Implementation of a Newton-Euler approach for updating state-dependent coefficients. • Finite-time SDRE to control a 20 DoFs, anthropomorphic dual-arm space manipulator. [ABSTRACT FROM AUTHOR]

This paper proposes a fractional-order time-varying sliding mode control method with predefined-time convergence for a class of arbitrary-order nonlinear control systems with compound disturbances. The method has global robustness and strongly predefined-time stability. All state errors of the system can converge to zero at a desired time, which can be set arbitrarily with a simple parameter. The strongly predefined-time convergence of the system is clearly demonstrated by the analytic expression of state error, which is obtained by solving fractional-order differential equations corresponding to the sliding mode function. The simulation results show that the proposed method still has good control performance in the presence of input saturation and external interference. • The main contributions of this paper are summarized as follows: • A predefined-time fractional-order time-varying sliding mode control scheme is proposed for a class of arbitrary order nonlinear control systems with complex disturbances. All state errors are simultaneously converged to zero by the scheme at a time, which can be presented by a simple parameter. • Different from most of the existing methods, this paper obtains the analytical expression of the state errors by solving the fractional-order differential equation to prove the predefined-time convergence of the system. • The fractional-order term and time-varying term are introduced into the proposed control scheme, which improves the control performance and makes the system have global robustness. The simulation results show that the proposed controller has strong robustness and resistance to input saturation. [ABSTRACT FROM AUTHOR]

In this paper, the energy efficiency of the widespread application of backstepping control to a class of nonlinear motion systems is investigated. A Switched Step Integral Backstepping Control (SSIBC) scheme is introduced to improve immunity to measurement noise and to increase the energy efficiency of conventional backstepping in practice. The SSIBC is realized by switching between two candidate controllers obtained at different steps of the iterative backstepping design process. A bi-state dependent hysteresis rule is developed to supervise stable switching between the different regimes in the presence of noise. The proposed method is experimentally verified on a MIMO twin rotor laboratory helicopter involving coupled nonlinear dynamics, inaccessible states and uncertainties. Experimental results show that in addition to a reduction in power consumption, the SSIBC reduces saturation of the control signal and visible motor jerking in contrast with conventional backstepping. Additional comparisons with a previously proposed optimized decoupling PID controller also show significant improvement in precision achieved with higher energy efficiency. Experimental results obtained with the introduction of an external disturbance into the system also show the robustness of the proposed SSIBC. • We propose a switched step integral backstepping control for nonlinear motion systems. • Experiments on a laboratory helicopter with time varying references show good system performance and energy efficiency. • The controller is robust to an external disturbance and reduces visible motor jerking. [ABSTRACT FROM AUTHOR]

In this paper, we address the swing-down control of the Acrobot, a two-link planar robot operating in a vertical plane with only the second joint being actuated. The control objective is to rapidly stabilize the Acrobot around the downward equilibrium point, with both links in the downward position, from almost all initial states. Under the conditions of no friction and measurability of only the angle and angular velocity of the actuated joint, we present a sinusoidal-derivative (SD) controller. This controller consists of a linear feedback of the sinusoidal function of the angle of the actuated joint and a linear feedback of its angular velocity. We prove that the control objective is achieved if the sinusoidal gain is greater than a negative constant and the derivative gain is positive. We establish crucial relationships between the relative stability of the Acrobot under the SD controller and its physical parameters, presenting analytically all optimal control gains. These gains minimize the real parts of the dominant poles of the linearized model of the resulting closed-loop system around the downward equilibrium point. We demonstrate that the resulting dominant closed-loop poles can be double complex conjugate poles, or a quadruple real pole, or a triple real pole, depending on the Acrobot's physical parameters. Simulation studies indicate that the proposed SD controller outperforms the derivative (D) controller in rapidly stabilizing the Acrobot at the downward equilibrium point. • The control goal is to rapidly stabilize the Acrobot in a downward position. • A sinusoidal-derivative (SD) controller has been developed to meet this objective. • The challenge of minimizing the real parts of the dominant poles is addressed. • Comprehensive analytical solutions for the optimal design of both gains are provided. • The introduced SD controller demonstrates improved control performance compared to other approaches. [ABSTRACT FROM AUTHOR]

Different works in literature have reported that nonlinear controllers based on the energy approach are not effective to completely swing-up an inverted pendulum subjected to friction. Most studies trying to solve this issue consider static friction models in the design of controllers. This consideration is mainly because the stability proof of the system with dynamic friction in closed-loop is difficult. Hence, this paper presents a nonlinear controller with friction compensation to swing-up a Furuta pendulum with dynamic friction. With this aim, we consider that only the active joint of the system is subjected to friction, which is represented via a dynamic model, namely, the Dahl model. We first present Furuta Pendulum dynamic model with dynamic friction. Then, by slightly modifying an energy-based controller that has been previously reported in literature and by including friction compensation, we propose a nonlinear controller that allows to swing-up completely a Furuta pendulum subjected to friction. The unmeasurable friction state is estimated through a nonlinear observer and a stability analysis of the closed-loop system is accomplished with the direct Lyapunov method. Finally, successful experimental results are presented for a Furuta pendulum prototype built by authors. This shows the effectiveness of the proposed controller in achieving a complete swing-up of the Furuta pendulum, in a time feasible for experimental implementation, and ensuring closed-loop stability. [Display omitted] The present paper proposes a nonlinear controller with dynamic friction compensation that experimentally achieves a complete swing-up for the Furuta pendulum in a short time, whose stability analysis is accomplished with the Lyapunov method • A nonlinear control to swing-up a Furuta pendulum with dynamic friction is proposed. • Control is an improved modification of an energy control previously reported. • Modification allows formally demonstrating swing-up accomplishment despite friction. • Three problems by friction in swinging-up inverted pendulums in practice are solved. • Improved performance of the control is successfully verified in practical application. [ABSTRACT FROM AUTHOR]

In this study, an intelligent PID (i-PID) controller is designed for position control of a nonlinear electro-hydraulic system with uncertain valve characteristics and supply pressure variations. The proposed controller uses estimation of ultra-local model of the system. To exhibit the capability of the proposed method, the controller parameters are optimized via the particle swarm optimization method through a nominal nonlinear model of the system. Then, the performance of the i-PID controller, parameters of which are optimized by using the nominal model, is examined under uncertainties caused by valve characteristics and supply pressure variations. Moreover, the friction between the piston and the hydraulic cylinder is also considered in experiments. A PID controller whose parameters are also optimized based on the same performance criteria, is used for comparison purposes with i-PID control both in simulations and experiments. Performance metrics of the controllers are examined and presented by employing two separate reference signals: Sine wave and ramp. The results show that the i-PID controller shows significantly better results than the classical PID controller in tracking the test signals under various supply pressures and valve modes. • Intelligent PID (i-PID) controller excels in industrial hydraulics. • It is easy to design and implementation. • i-PID control is implemented experimentally in an electro-hydraulic system. • Parameters of i-PID controller are optimized via particle swarm optimization. • The controller tested against uncertainties (supply pressure and valve variations). • i-PID outperforms optimized PID for sine and ramp tracking in diverse conditions. [ABSTRACT FROM AUTHOR]

This paper proposes a method of using multiple spacecraft flying in formation in an artificially reduced halo orbit around the 2nd Lagrange point in the Sun–Earth system (SEL2) to make interferometric observations. One of the requirements for interferometric observations is to collect baseline vectors between telescopes or antennas. A shape-based approach is introduced to design a formation flight orbit that spirally spreads to satisfy this requirement. In this approach, orbits are designed on the basis of a linear theory. However, the formation orbits based on the linear theory quickly diverge because of the unstable dynamics around the SEL2. Therefore, the state-dependent Riccati equation, which allows for nonlinear control, is applied to orbit maintenance. The control system consists of two components: one for maintaining the reference orbit around the SEL2 and the other for controlling the relative position between the multiple spacecraft. The performance of the developed formation flight system is verified through a numerical simulation, confirming that the position accuracy requirement of the infrared interferometer is satisfied. It is also shown that both controls can be achieved with a low-thrust magnitude by using an electric propulsion system. • Formation flights around the Lagrange points are useful for interferometer. • An artificial halo orbit is designed with a reduced radius and a fixed shape. • Spacecraft formations are designed to collect more baseline vectors. • A nonlinear control is designed using the state-dependent Riccati equation. [ABSTRACT FROM AUTHOR]

The piezo-driven nanopositioning stage (PNS) is a key device to provide fast and precise motions for applications such as micromanipulation, microfabrication, and microscopy scanning. However, inherent nonlinearities associated with system perturbations bring difficulties to controller design. Regarding repetitive tasks for a PNS, existing control schemes are mainly dedicated to model inversion-based iterative learning control (ILC), which relies heavily on model accuracy. In this paper, a novel online identification and control scheme named neural network-based ILC (NN-ILC) is proposed for repetitive tracking of the PNS. The ILC scheme reduces repetitive errors due to the linear dynamics and invariable disturbance during each iteration. Neural networks are integrated into the ILC scheme to minimize the residual non-repetitive errors resulting from unknown nonlinear dynamics and model perturbations. Convergence results in both the time and iteration domains are demonstrated according to the Lyapunov stability theory. Comprehensive experiments of sinusoidal and triangular tracking references with different frequencies (5 ∼ 20 Hz) and different peak-to-peak amplitudes (5 ∼ 20 μ m) are conducted on a real-time control testbed. Results show that the root mean square error of the proposed NN-ILC for 20 μ m tracking cases is improved by up to 37% from feedback proportional-derivative (PD) control with neural networks and by up to 20% from feedforward PD-type ILC. • Developing a neural network-based iterative learning control scheme. • Demonstrating the stability in both time and iteration domain for the controller. • Figuring out the implementation procedure of the proposed NNILC scheme. • Conducting comprehensive comparisons between NNILC with typical controllers. [ABSTRACT FROM AUTHOR]

The performance of a photovoltaic power system is heavily influenced by mismatches, for example, partial shading effects. In literature, it lacks of a scrupulous study on intelligent control designs whose transient responses and steady state responses are not directly given when achieving the goal of global maximum power point tracking (GMPPT). A novel and systematic control design approach is proposed mathematically to derive explicit discrete controllers for the overall GMPPT performance. Specifically, the new algorithms of nonlinear function (NF) based particle swarm optimization (PSO) and ordered excitation (OE) are incorporated into the extreme seeking controller for the enhancement of both transient and steady state responses when fulfilling the extreme seeking task. The explicit control functions are easy to implement in the applications. Both the simulation based analysis and experimental study are carried out in a statistical manner in order to evaluate the proposed controller through a number of control performance indicators. A comparison analysis of the statistical data reveals that both simulation and experimental results agree with the theory where both algorithms of NF-PSO and OE play a role to improve transient responses and steady state responses for the global extreme seeking. Meanwhile, the proposed intelligent controller outperforms the classical benchmark in tracking the GMPP. The insightful and instructive control design tool is promising in both academia and engineering. • An explicit ESC of OE-NF-PSO is proposed. • The algorithm of OE is introduced to reduce the oscillations. • The algorithm of NF-PSO helps improve the global extreme seeking ability. • New control norms are defined for a comprehensive analysis. • The analysis of both numerical and experimental results is carried out. [ABSTRACT FROM AUTHOR]

This paper suggests a nonlinear controller of a Static Synchronous Series Compensator (SSSC) and a doubly-fed induction generator (DFIG) for transient stability enhancement by transient energy function (TEF) technique and super-twisting differentiator in the multi-machine power system. Initially, the TEF approach is employed to damping control and stability enhancement in a multi-machine power system including an SSSC, DFIG, and synchronous generator (SG). Then, the signals of time-derivative in the controller with a super-twisting differentiator are estimated. The significance and novelty of this work are the employs of the TEF method obtained for the multi-machine power system containing DFIG and SG. Another novelty is the use of the DFIG and SSSC simultaneous control whose uncertain parameters are estimated with a super-twisting differentiator. The feature of the nonlinear control approach is robust versus modifications in the topology of the system. Simulation is performed on the IEEE 9-bus system to appraise the operation of the nonlinear controller approach compared to back-stepping and sliding mode control. The simulation results demonstrate that the nonlinear controller approach satisfactorily reduces the first swing of oscillations. • DFIG model is similar to a one-axis model of an SG. • The TEF is obtained in the power system with DFIG and SSSC. • Control laws are achieved with three control variables DFIG and SSSC. • The time-derivative signals of the DFIG and SSSC control are estimated based on a super twisting differentiator. [ABSTRACT FROM AUTHOR]

This paper proposes a new explicit model predictive control (EMPC) scheme of constrained nonlinear systems with unknown but bounded input disturbances. Firstly, support vector machine is used to learn internal and external approximations of the feasible state space of the EMPC. Then, the control surface on the feasibility of EMPC is constructed by a backpropagation neural network (BPNN). The finite horizon optimal control solution to the EMPC can be computed from real-time data by training the control surface. The proposed EMPC is also suitable for nonlinear systems with higher dimensions in terms of reducing online computational burdens and enhancing control accuracy. Next, the Hoeffding's Inequality is used to ensure that the EMPC law computed by the BPNN approximation complies with the specified range with a high level of confidence. Moreover, some conditions are obtained to guarantee the stability and recursive feasibility of the EMPC with probabilistic assurances. Finally, a 160 MW boiler-turbine system is employed to verify the effectiveness and applications of the proposed method. • Proposing an ENMPC algorithm for boiler-turbine systems with input disturbances. • Modelling the learning errors as the input disturbances. • Using SVM to learn approximations of the boundary of the feasible state space. • By BPNN constructing the control inputs of the EMPC. • Introducing Hoeffding's Inequality, probabilistic verification of stability. [ABSTRACT FROM AUTHOR]

Disturbances in iterative learning control (ILC) may be amplified if these vary from one iteration to the next, and reducing this amplification typically reduces the convergence speed. The aim of this paper is to resolve this trade-off and achieve fast convergence, robustness and small converged errors in ILC. A nonlinear learning approach is presented that uses the difference in amplitude characteristics of repeating and varying disturbances to adapt the learning gain. Monotonic convergence of the nonlinear ILC algorithm is established, resulting in a systematic design procedure. Application of the proposed algorithm demonstrates both fast convergence and small errors. [ABSTRACT FROM AUTHOR]

The TOPAZ-II thermionic space reactor system, which was designed by the Soviet Union, is characterized by its high degree of nonlinearity and positive temperature reactivity feedback. The thermionic space reactor exhibits characteristics of high inertia and significant delay in controlling its electrical power and outlet temperature. The simple PID controller is difficult to achieve good performance. To carry out controller design for thermionic space reactor, the simulation platform for thermionic space reactor is developed based on coupling between reactor system thermal-hydraulic code RESYS and control system simulator in this study. After that, based on the cascade control strategy and gain-scheduling, the reactor thermal controller, electric power controller, outlet temperature controller applicable for the full power range is designed with transfer function model and frequency domain analysis method. To validate the nonlinear electric power controller performance, the continuous minor step disturbances, major step disturbances, and ramp variation of electric power setpoint is simulated. The performance of outlet temperature controller is verified with the simulation result of step and ramp variation of outlet temperature setpoint. Thereafter, the start-up process of the thermionic space reactor TOPAZ-II is simulated and analyzed. The simulation result reveals that the controller designed in this paper can overcome the nonlinearity of the thermionic space reactor system and has good performance throughout the entire power range. Compared to traditional simple PID controller, the cascade controller has better performance and can achieve good control performance even in situations where simple PID controllers cannot function properly. • The simulation platform of TOPAZ-II thermionic space reactor is developed. • The nonlinear cascade controller for TOPAZ-II reactor system is established. • Cascade controller parameters are optimized based on frequency domain analysis method. • The designed cascade controller achieved better performance compared to PID controller. • The start-up of TOPAZ-II reactor under the established cascade controller is analyzed. [ABSTRACT FROM AUTHOR]

Proton exchange membrane fuel cells (PEMFCs) are being extensively studied for large-scale applications. The need for reliable and safe system integration processes emphasizes the importance of health-conscious control research. Considering their high-frequency operation and load variations, the reliability of PEMFCs can be compromised by mechanical failures within air supply systems. Therefore, this paper proposes an adaptive control strategy with fault-tolerant objectives for regulating the oxygen excess ratio (OER). Specifically, it addresses two common faults within air compressors, namely compressor overheating and increased mechanical friction. While these faults have been studied in fault diagnosis research, their treatment within the context of fault-tolerant control is relatively uncommon. To ensure reliable OER regulation under multiple fault occurrences, estimator-based parameter adaptation laws are firstly derived using Lyapunov theory during the stability demonstration process. Then, the baseline controller is designed using an extended state observer and feedback linearization, with a clear presentation of the existence and stability of the state transformation. Furthermore, extensive numerical tests are conducted to demonstrate the effectiveness of the proposed control strategy. The proposed adaptive control strategy ensures consistent regulation outcomes without compromising performance under healthy conditions, highlighting its potential for large-scale application as a standard control approach in practical applications. • Air compressor faults like overheating and friction are managed with fault-tolerant control. • Lyapunov theory deduces analytical estimators for fault occurrence adaptation. • State transformation stability in feedback linearization is clearly demonstrated. [ABSTRACT FROM AUTHOR]

Multirotor aerial vehicles are versatile flying robots that perform hovering, vertical take-off and landing, and aggressive maneuvers in a 3D environment. Due to their underactuated nature, the aerial vehicles' position and orientation cannot be controlled independently. For this reason, most of the quadrotors' tasks involved position tracking or regulation tasks. This paper focuses on the position-tracking problem of quadrotors using the reduced orientation of the vehicle, meaning that only two degrees of freedom of the robot's orientation are controlled. We propose an almost global exponential reduced attitude control law that aligns the aerial robot's thrust direction with the desired force that drives the robot along the desired position trajectory. For the translational subsystem, we propose a dynamic control law that drives the position and velocity of the quadrotors asymptotically to the desired trajectories. The proposed attitude control law is computationally simple, and thus, it is suitable to run on board. Finally, we provide experimental results performed on a low-cost quadrotor and a comparison study with a full-attitude controller to illustrate the performance and advantages of the proposed control laws. • Position trajectory tracking is achieved by properly controlling the quadrotor's reduced attitude. • The proposed reduced attitude control law guarantees almost global exponential stability. • The position controller generates a bounded signal and guarantees asymptotic tracking of the reference signals. • The effectiveness of the proposed feedback control laws was successfully validated by real-time experiments. [ABSTRACT FROM AUTHOR]

Control of electro-booster is crucial for vehicle safety. Traffic accidents occur due to unmanageable control errors in the electro-booster system and tire lock-up caused by excessive braking force. Achieving consistent prescribed performance and anti-lock braking presents a challenge due to the system nonlinearity and time-varying uncertainties. In this context, this study introduces a constrained prescribed performance control (CPPC) approach for the electro-booster. We formulate the prescribed performance and the anti-lock braking as constraints of control error and input, respectively. A diffeomorphism approach is proposed to establish a mapping between an unconstrained system and the electro-booster system with constraints. No linearization are invoked in the control design and no extra anti-braking system is needed. Experiments and simulations have demonstrated that the desired braking actions can be accurately executed under uncertainties, while guaranteeing both prescribed performance and anti-lock braking. • Limit the control input to a safe range through a diffeomorphism approach. • Precise electro-booster control is achieved through prescribed performance control. • The proposed control guarantees prescribed performance under uncertainty and input constraint. [ABSTRACT FROM AUTHOR]

Nonlinear, imbalanced, and constant power loads pose significant technical and power quality challenges in both AC and DC microgrids. Hybrid AC/DC microgrids further compound these complexities. In response, this paper presents a novel hierarchical control scheme comprising primary and secondary layers for such microgrids. The proposed scheme introduces innovative cooperative voltage and frequency secondary control methods, complementing conventional droop-based primary controllers. This hierarchical structure aims to provide acceptable voltage and frequency regulations, as well as power sharing in both AC and DC sub-grids, mitigating issues arising from various loads. Specifically, the DC sub-grid maintains its stability in the presence of constant power loads, while the AC bus output voltages maintain sinusoidal waveforms. Finally, we conduct digital time-domain simulation studies on a test microgrid system using the MATLAB/Simulink environment to assess the performance of the proposed control strategy. We compare the results with previously reported methods. The results demonstrate that the proposed methods effectively share power with reduced overshoot and faster convergence toward desired values compared to conventional controllers. Simulation analyses validate the superiority and efficacy of the proposed control scheme. • Novel distributed secondary control for voltage/frequency regulation and power sharing. • Suppresses non-linearity and imbalance by integrating positive/negative current components. • Achieving better convergence speed and less over/undershoot by the proposed structure. • New distributed control strategy for DC voltage restoration using an additional feedback loop. • Effective in voltage adjustment, current sharing, and stability in presence of CPLs. [ABSTRACT FROM AUTHOR]

Due to complicated dynamics, wind turbines' governing equations are subject to uncertainties and unknown disturbance sources. Despite uncertainties and disturbance sources, the paper's focus is to design an adaptive controller that enables trajectory-tracking with a zero-converging tracking error. As the main result of a zero tracking error, the turbine can operate at maximum power efficiency. In addition, novel Lyapunov functions are proposed introducing auxiliary adaptive terms to result in closed-loop asymptotic stability in the presence of a non-affine controller input, uncertainties, and unknown disturbance sources. Considering the turbine dynamics, one can divide the wind turbine control problem into torque and pitch control phases. For addressing the nonlinearities and uncertainties of the dynamics in each phase, RBF neural networks are utilized to develop novel control and adaptive laws. To address the non-affine dynamics stemming from the pitch angle, a neural network alongside the implicit function and mean-value theorems are utilized to transform the dynamics into the control affine form. Several auxiliary adaptive variables are proposed in the transformation procedure, leading to closed-loop asymptotic stability. Moreover, using the Lyapunov stability analysis, closed-loop asymptotic stability is obtained for each phase. In the end, simulation results are presented to verify the analytical results where the proposed controller's performance is compared to that of an existing method in different scenarios. The proposed controller's simulation results suggest dramatic improvement over those of the existing method in both trajectory-tracking and required control action. • An adaptive robust controller for non-affine systems, guarantying asymptotic stability. • An adaptive neural network to cope with uncertainties and unknown disturbance sources. • Improvement of the adaptive laws to prevent the possibility of chattering. • Novel cross-term Lyapunov functions, relating the dynamics and approximation errors. • Significant performance improvement of the presented method over existing ones. [ABSTRACT FROM AUTHOR]

This paper presents a linear-based gain-determining method for nonlinear adaptive backstepping controllers. Usually, the gains for nonlinear controllers are tuned by the trial and error method. This method becomes more difficult as the number of gains increases. A user-friendly method is proposed in this work to deal with the problem. Firstly, a linear auxiliary system is formed by separating the linear parts from the nonlinear system. Then, linear state-space techniques are used to determine the gains for state-feedback by the linear auxiliary system. After that, by converting the state-feedback gains to backstepping gains, the gains of the nonlinear backstepping controller can be determined. The proficiency of the gain-determining method is proved by simulations with two linear techniques. • Linear techniques can be used for the gain determination for nonlinear control systems. • The ascending gain solution performs better than other solutions in general. • The resulted performance of the nonlinear systems is similar to that of the desired linear systems. [ABSTRACT FROM AUTHOR]

In this study, a Lyapunov-based model predictive control (LMPC) method is developed to address the trajectory tracking problem of autonomous hovercrafts subjected to unknown complex disturbances from ocean environments and practical constraints of marine surface vessels, such as actuator increment limitations and saturation. Initially, the novel LMPC algorithm is applied to enhance tracking performance through rolling optimization and online optimization. Subsequently, a nonlinear disturbance observer is designed to estimate external disturbances caused by wind and dynamics uncertainties. Furthermore, to theoretically ensure control stability, contraction constraints are established using the nonlinear backstepping control method. This approach provides the essential conditions for the system's robustness and stability. Finally, the superiority and robustness of the designed LMPC trajectory tracking method are demonstrated through numerical simulations conducted in a marine environment. • Applying the LMPC algorithm to significantly enhance the hovercraft trajectory tracking performance and robustness under complex constraints. • A novel demonstration of closed-loop stability and recursive feasibility is provided for the LMPC controller design without local linearization. • Rolling optimization is applied to derive the final solution, improving control performance of the optimal solution, given the underactuated characteristics during high-speed manoeuvres of hovercrafts. [ABSTRACT FROM AUTHOR]

The minimum value of the safety factor profile is related to the magnetohydrodynamic (MHD) stability of the plasma confined in a tokamak. Therefore, active control of the minimum safety factor may mitigate MHD instabilities that can degrade or even terminate plasma confinement. Typically, in most tokamak scenarios, the minimum safety factor evolves spatially with time, i.e., the location at which the safety factor achieves the minimum value changes with time. In addition to the inherent nonlinearities in the minimum safety factor evolution, its spatial variation makes the control design challenging. In particular, complexity in control design may arise from the need for time-dependent nonlinear models that account for spatial variation of the minimum safety factor. Furthermore, the minimum safety factor may drift to locations where the actuator authority is low. The problem of minimum safety factor control with target location tracking and moving electron cyclotron current drive (ECCD) is addressed in this work. A nonlinear time-dependent model that incorporates the spatial variation of the minimum safety factor is presented. A nonlinear controller based on optimal feedback linearization is developed to track a target minimum safety factor. The proposed controller treats the ECCD position as a controllable variable. In other words, the controller prescribes the ECCD position (in addition to the non-inductive powers) in real time based on an optimal criterion that is defined a priori. This work also presents the steps necessary to integrate the minimum safety factor controller with a total energy controller to achieve multiple control objectives simultaneously. The proposed integrated control algorithm is tested using nonlinear simulations in the Control Oriented Transport SIMulator (COTSIM) for a DIII-D tokamak scenario. • A control-oriented model for minimum safety factor is developed. • A nonlinear controller for target minimum safety factor tracking is synthesized. • Spatially variable ECCDs are exploited for enhanced control. • Simulation studies are presented for fixed & moving ECCD cases. [ABSTRACT FROM AUTHOR]

Incremental Nonlinear Dynamic Inversion (INDI) has received substantial interest in the recent years as a nonlinear flight control law design methodology that features inherent robustness against bare airframe aerodynamic variations. However, systematic studies into the robust design benefits of INDI-based control over the classical divide-and-conquer philosophy have been scarce. To bridge this gap, this paper compares the setup of hybrid INDI with a standard industry benchmark that is based on two-degree-of-freedom gain-scheduled proportional-integral-derivative control. This is done on an architectural basis and in terms of achievable robust stability and performance levels with respect to a common set of design requirements. To this end, a non-smooth, multi-objective H ∞ -synthesis algorithm is used that incorporates mixed parametric and dynamic uncertainties in the design objective and constraints. It is shown that close similarities exist between hybrid INDI design and gain-scheduled PID control, which leads to virtually equivalent robustness and performance outcomes in both linear time-invariant and linear time-varying contexts. It is therefore concluded that the main benefit of the hybrid INDI does not lie in improved robustness properties per se , but in the opportunity to perform modular robust design in an implicit model-following context. Specifically, this implies that the areas of flying qualities, robustness, and nonlinear implementation are directly visible and accessible in the control law structure. [ABSTRACT FROM AUTHOR]

Iterative learning control (ILC) and repetitive control (RC) can lead to high performance by attenuating repeating disturbances perfectly, yet these approaches may amplify non-repeating disturbances. The aim of this paper is to achieve both perfect, fast attenuation of repeating disturbances and limited amplification of non-repeating disturbances. This is achieved by including a deadzone nonlinearity in the learning filter, which distinguishes disturbances based on their different amplitudes to apply different learning gains. Convergence conditions for nonlinear ILC and RC are developed, which are used in combination with system measurements in a comprehensive design procedure. Experimental implementation demonstrates fast learning and small errors. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative control strategy for a dual active bridges DC–DC converter employed to regulate voltage levels between two feeders in a DC microgrid. The controller is specifically designed to regulate the output voltage at a predetermined reference value and to ensure a zero mean value for both primary and secondary currents of the high-frequency transformer, regardless of any imbalance in one of the active bridges. This is particularly important in the face of potential imbalances in one of the active bridges resulting from construction disparities in converters or variations in conduction resistances in power transistors. Given the nonlinear nature of the converter, the controller is designed using feedback linearization. The output is selected with a relative degree equal to the system order, resulting in a stable controller exhibiting good dynamic performance under scenarios such as reference changes, linear load fluctuations, and the integration of constant power loads. The performance of the proposed control strategy is validated through both simulation and experimental results. [ABSTRACT FROM AUTHOR]

Track Nonlinear Energy Sinks (T-NES) are Pendulum Tuned Mass Dampers (PTMDs) whose nonlinear restoring forces are obtained from curved path shapes. They combine the abilities of traditional spring-based NESs with the operational advantages of PTMDs. T-NES can resonate with broad frequency content, becoming effective even under damage to the host structure originating from strong ground motions. In the published literature, the integration of Friction Dampers (FDs) into T-NESs (so-called T-NES Type II) has only been studied on PTMDs with circular tracks, and in deterministic settings. Herein, a novel Reliability-Based Design Optimization (RBDO) procedure is presented to find the optimal track shape of T-NES Type II in buildings subjected to earthquakes. The objective is to minimize expected life-cycle damage costs corresponding to slight damage, moderate damage, and extensive damage limit states. A set of rational functions encompassing a wide range of generic curvatures is constructed to describe the T-NES track shape. The nonlinear description is used for restoring force and also in the dissipative mechanism. The case study is a medium-rise building located in Chile. The results indicate that, for the studied building, the optimal path is multimodal, and quite different track profiles can significantly reduce oscillation of the host structure. • Optimal path shape of friction-based Track-Nonlinear Energy Sinks (TNES II) is obtained. • RBDO to minimize lifecycle costs of buildings subjected to ground accelerations. • Pushover analysis to evaluate stiffness reduction in damaged limit states. • Optimal path is multimodal, varying from circle to bi-stable shape. [ABSTRACT FROM AUTHOR]

This paper develops a novel Lyapunov function candidate for control of the three-dimensional (3-D) overhead crane, which yields a nonlinear controller to inject active damping. Different from the existing passivity-based controls that employ either the angular displacement or its integral as passive elements, the proposed controller incorporates both of them in a new coupled-dissipation signal, thus significantly enhancing the closed-loop passivity. Owing to the improved passivity, the proposed controller ensures the effective suppression of payload oscillations and robustness. Moreover, the control design is extended with the hyperbolic tangent function to prevent overdriving the trolley. The asymptotic stability is guaranteed by LaSalle's invariance principle. The transit performance of the closed-loop system, including robustness, is validated by numerical simulations. • The inherent nonlinearities of the 3-D overhead crane are reserved in the design process. • A novel Lyapunov function candidate is constructed based on the coupling solution. • The passivity of the closed-loop system is improved by introducing a new composite signal. • The hyperbolic tangent function is employed to achieve a soft trolley start. [ABSTRACT FROM AUTHOR]

This paper presents a voltage control mode (VCM)-based super-twisting algorithm-sliding mode controller (STA-SMC) and current control mode (CCM)-based STA-SMC for islanded and grid-connected operations of single-phase inverters interfaced with distributed energy resources (DERs), respectively. The external disturbances are modeled by considering the effects of load currents or load voltages depending on operational modes whiles parametric uncertainties are modeled based on their variations from nominal values. Therefore, the proposed controllers are robust against external disturbances, parametric uncertainties, and variations in loading conditions. Simulation studies are conducted in the MATLAB/Simulink platform for both single and multiple DERs which are interfaced through single-phase inverters to the main grid or loads. The results are also analyzed through comparative studies with different controllers and it is found that the proposed controllers perform better than existing controllers. • A VCM-based STA-SMC is designed for islanded operations of DERs. • A CCM- STA-SMC is designed for grid-connected operations of DERs. • The robustness is analyzed against external disturbances and parametric uncertainties. • Performances are evaluated under different loading conditions. [ABSTRACT FROM AUTHOR]

The field of unmanned aerial vehicles (UAVs) has grown in the last years, showing its utility in broader applications. For instance, in surveillance, precision agriculture, pack delivery, among others. The UAVs characteristics demand more suitable configurations for increasing their flight time, maneuverability, stability, and reliability for attending a growing quantity of services. One of the UAV configurations that has gained popularity in the last years is the Convertible Unmanned Aerial Vehicle (CUAV). This paper aims to provide a control strategy to stabilize the CUAV in all the flight modes: hover, cruise, and transition mode, in which the CUAV changes between hover and cruise flight mode. For that, we propose longitudinal modeling that considers realistic aerodynamics and even disturbances. This model presents a precise balance between complexity and practicality for control implementations. The control algorithm design is based on the Lyapunov stability theory and uses saturation functions intending not to saturate the actuators. Besides, the control algorithm does not include any switching function, is easy-to-implement, and demands the usually available feedback in the vast majority of low-cost commercial autopilots. The control allocation problem for this control is also solved. A mathematical proof based on Lyapunov theory demonstrates that the proposed controller performs the closed-loop system globally exponentially stable. Simulation and real flight experiments conducted with the CUAV demonstrate the effectiveness of theoretical results. Moreover, we present several comparative studies with the state of the art that demonstrate the paper's contribution to the field of convertible aerial vehicles. • A tilt-rotor convertible unmanned aerial vehicle (CUAV) is presented. • The CUAV is modeled and stabilized in hovering, cruise, and transition flight modes. • A nonlinear smooth control solves the transition maneuver problem. • Several comparisons with the state-of-the-art are given. • Extensive flight experiments in the CUAV real platform are presented. [ABSTRACT FROM AUTHOR]

This research extends the design of adaptive passivity-based controllers (APBC), proposing a normalized APBC (NAPBC) for nonlinear dynamical systems with a direction of control unknown. The plant also has an accessible single-input and a single-output, smooth behavior, linear explicit parametric dependence, and unknown parameters. The proposed method can handle unknown control direction through an alternate and more straightforward method than Nussbaum gains, having two fewer parameters. We present the stability proof of the controlled system. Besides, the proposed NAPBC expands the tuning method for normalized fixed gains or time-varying gains, reducing the trial and error procedure. Finally, we apply the proposed methodology step by step to a conical tank-scale pilot plant. Comparative experimental results show the proposed NAPBC has better indexes ISI, Ess, MO, IAE, and Ts. [ABSTRACT FROM AUTHOR]

In order to solve the nonlinear control problem of DC-DC Buck-Boost converter in switching power supply, the synergetic control method is adopted and applied to DC-DC Buck-Boost converters. Firstly, according to the characteristics of DC-DC Buck-Boost converter, we choose an improved macro-variable during the design of synergetic controller, which reduces the dynamic response time of the system. The synergetic control law of the system is also derived. Then, considering of the system robustness to the input voltage changes, we add a compensation amount to the control law, which can improve the control precision and make the system a good inhibitory effect to parameter change. Finally, the simulation results show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Centralized model predictive control is impractical for many complex systems due to communication burden and robustness issues. For these systems, distributed model predictive control (DMPC) is an alternative control strategy. In DMPC, the use of nonlinear first-principle model improves the prediction accuracy. However, it also brings about computational delay due to time-consuming optimization of large, non-convex nonlinear programs, which can then degrade the control performance. In this work, a fully distributed nonlinear model predictive control (DNMPC) algorithm is developed to accelerate control feedback. The input computation procedure contains background and online stages, in which prediction–correction mode is applied. In the background stage, the future state is predicted one step forward based on the nominal plant model. Each controller optimizes its own local input and exchanges latest information with other controllers to improve decision making. After distributed optimization, the local controllers collect optimality information to prepare for future computation. When the true state is available, the state prediction error can be calculated. Each controller formulates its local sensitivity equation based on parametric sensitivity. All the sensitivity equations are solved in parallel with application of the Jacobi iterative method. After solution, the nominal optimum is updated with the correction vector and then implemented to the plant. The theoretical analysis of the proposed method is presented. Four case studies are given to demonstrate the effectiveness of the proposed algorithm. • A fast, fully distributed model predictive control algorithm is proposed for nonlinear systems. • Prediction–correction mode is applied in the proposed method. • The future inputs are computed in background with advanced-step distributed optimization. • The local sensitivity equations are solved in parallel through Jacobi iteration. computation. • The closed-loop system is proved to be input-to-state practical stable. [ABSTRACT FROM AUTHOR]

A novel practical fixed-time command-filtered backstepping strategy for a hydraulic turbine regulating system (HTRS) is developed in this paper. The developed controller is designed with the help of a combination of command-filtered backstepping and practical fixed-time stability theory. Based on this scheme, the obtained control strategy is utilized to ensure that the equilibrium point is practically fixed-time stable, and all signals of the closed-loop system are bounded within a fixed time. The main contributions of this paper are threefold: (i) The control scheme for frequency regulation of the HTRS is proposed to deal with the problem of the "explosion of terms" caused by conventional backstepping design. (ii) The proposed practical fixed-time control law can guarantee superior stabilization with a more precisely bounded convergence time, and (iii) The proposed controller performs well, simultaneously offers better transient performance, and overcomes three important drawbacks arising in the current results of fixed-time synergetic controllers. The strategy's effectiveness and feasibility are validated in a nonlinear model of the HTRS connected to a single-machine infinite bus power system. The numerical simulation indicates that the frequency regulation and improved transient performances in fixed time are achieved based on the proposed strategy. Further, the presented control reduces the oscillations rapidly and performs better than fixed-time synergetic control and modified fixed-time synergetic control approaches. • A novel fixed-time command-filtered backstepping control scheme for frequency regulation of the HTRS is proposed. • The proposed practical fixed-time control law is capable of guaranteeing superior stabilization with a bounded convergence time. • The obtained bounded convergence time is more accurately computed than the one in the literature. • In comparison with fixed-time synergetic controllers, the proposed control law performs well and offers better transient performances. [ABSTRACT FROM AUTHOR]

Due to complex electrochemical and thermal phenomena, varying operations towards automotive applications, and vulnerable ancillaries in proton exchange membrane fuel cells (PEMFCs), fault diagnosis and fault-tolerant control (FTC) design have become important aspects to improve the reliability, safety and performance of PEMFC systems. This paper presents a novel FTC scheme for automotive PEMFC air supply systems via coordinated control of the air flow rate and the pressure in cathodes. A dynamic surface triple-step approach is first proposed considering nonlinear dynamics and the multi-input multi-output (MIMO) property, which combines the advantage of dynamic surface control in avoiding an "explosion of complexity" and the advantage of triple-step control in guaranteeing a simple structure and high performance. The normal case, the faulty case at the supply manifold and the faulty case in the back pressure valve are considered in the FTC design, with the stability of the overall system proved using Lyapunov methods. MATLAB/Simulink simulations with a high-fidelity PEMFC model verify the effectiveness of the proposed FTC scheme in regulating the air flow rate and oxygen excess ratio and maintaining the pressure of the cathode at a desired level even under faulty conditions. • The air supply system for proton exchange membrane fuel cells (PEMFCs) is modeled. • Valve stuck and supply manifold leakage faulty cases are considered. • A fault-tolerant control (FTC) scheme is proposed by a triple-step approach. • The stability of the overall system is proved using Lyapunov method. • A high-fidelity PEMFC model is applied to confirm the proposed FTC method. [ABSTRACT FROM AUTHOR]

This paper proposes a saturated smooth adaptive controller for regulating a certain type of underactuated Euler–Lagrange systems (UELSs) with modeling uncertainties and control saturations based on a singular perturbation approach. Compared with relevent literature, the advantages of the proposed controller include: (1) it renders the UELS semiglobally asymptotically track the desired position without the violation of control input constraints; (2) high-order derivatives of positions are not required in its implementation. The Hoppensteadt's Theorem is employed to show that the proposed saturated controller renders the UELS semiglobally asymptotically stable about the desired set point with the satisfaction of control input constraints. The control effectiveness is validated by simulations on a two-link compliant robot arm. • A saturated adaptive controller is proposed for underactuated Euler–Lagrange systems. • An adaptive estimator with a prior designed bound is proposed for the gravitational torque. • A proportional-derivative control term is designed for the slow-varying subsystem. • The Hoppensteadt's Theorem is applied to prove semiglobal asymptotical stability. [ABSTRACT FROM AUTHOR]

Back-stepping design method is widely used in high-performance tracking control tasks As is known to all, the controller based on back-stepping design will become complex as the model order increases, which is the so called "explosion of terms" problem. In this paper, a tracking differentiator (TD) based back-stepping controller is proposed to handle the "explosion of terms" problem. Instead of calculating the derivatives of intermediate control variables through tedious analytical expressions, for the proposed method, the tracking differentiator is embedded into each recursive procedure to generate the substitute derivative signal for every intermediate control variable. As a result, the complexity of implementation procedure of back-stepping controller is significantly reduced. The discrepancies between the derivative substitutes and the real derivatives are considered. And the effects on control performances caused by the discrepancies are analyzed. In addition to giving the theoretical results and the stability proofs with Lyapunov methods, the developed controller design method is evaluated through a series of experiments with a hydraulic robot arm position serve system. The control performance of the proposed controller is verified by the experiments results. • A practical back-stepping controller design method is presented. • The tracking differentiator based back-stepping controller is developed for the valve-controlled actuator position tracking system. • The proposed method is implemented on a robot arm test rig and its performance is verified experimentally. [ABSTRACT FROM AUTHOR]

In this paper, we generalize our previous results of Newton-based extremum seeking of higher derivatives via predictors with averaging-based estimates for uncertain delays. We show necessary conditions for the robustness to small delay uncertainties of the proposed extremum seeking controller with predictor feedback. Local stability and exponential convergence to a small neighborhood of the unknown extremum can still be guaranteed. A numerical simulation example is presented to illustrate the performance of the predictor-based control scheme for uncertain time-delay compensation. [ABSTRACT FROM AUTHOR]

Wastewater treatment is a problem known to humankind for centuries. The quality of treated sewage determines the condition of reservoirs around the world. Control of such a complex and nonlinear system as a wastewater treatment plant requires thorough knowledge of the process. The paper presents a hierarchical control system of a Sequencing Batch Reactor (SBR) in Wastewater Treatment Plant (WWTP) taking into account a model based on actual measurements taken from a WWTP in Swarzewo, Poland. The authors designed and implemented a nonlinear model predictive controller (MPC) that allows for the optimal implementation of the desired DO level while minimising the operation of actuators (aeration system). The design description of the predictive controller was associated with the need to specify the performance function and define the optimisation problem. In a two-layer structure, a supervisory controller was implemented based on an actual time-based controller in Swarzewo WWTP. The overview showed the improved performance of the treatment plant and the versatility of the created solution. Results of simulation tests for the wastewater treatment plant case study are presented. • Dissolved oxygen control is very important for WWTP energy efficiency. • The process of designing a hierarchical control system of a SBR has been presented. • Nonlinear MPC has been applied for optimal implementation of the set DO trajectory. • Results of simulation tests for WWTP case study have been presented. [ABSTRACT FROM AUTHOR]

[Display omitted] • This article proposes a new robust nonlinear controller that stabilizes a chaotic finance system in a finite-time without cancellation of the spacecraft's nonlinear terms, it improves the efficiency of the closed-loop. • It accomplishes an oscillation-free faster convergence of the perturbed state variables to the desired steady-state. • The proposed controller is insensitive to the parameter uncertainties of the nonlinear terms and exogenous disturbances. • The paper performs a comparative study to verify the performance and efficiency of the proposed controller. Robust, stable financial systems significantly improve the growth of an economic system. The stabilization of financial systems poses the following challenges. The state variables' trajectories (i) lie outside the basin of attraction, (ii) have high oscillations, and (iii) converge to the equilibrium state slowly. This paper aims to design a controller that develops a robust, stable financial closed-loop system to address the challenges above by (i) attracting all state variables to the origin, (ii) reducing the oscillations, and (iii) increasing the gradient of the convergence. This paper proposes a detailed mathematical analysis of the steady-state stability, dissipative characteristics, the Lyapunov exponents, bifurcation phenomena, and Poincare maps of chaotic financial dynamic systems. The proposed controller does not cancel the nonlinear terms appearing in the closed-loop. This structure is robust to the smoothly varying system parameters and improves closed-loop efficiency. Further, the controller eradicates the effects of inevitable exogenous disturbances and accomplishes a faster, oscillation-free convergence of the perturbed state variables to the desired steady-state within a finite time. The Lyapunov stability analysis proves the closed-loop global stability. The paper also discusses finite-time stability analysis and describes the controller parameters' effects on the convergence rates. Computer-based simulations endorse the theoretical findings, and the comparative study highlights the benefits. Theoretical analysis proofs and computer simulation results verify that the proposed controller compels the state trajectories, including trajectories outside the basin of attraction, to the origin within finite time without oscillations while being faster than the other controllers discussed in the comparative study section. This article proposes a novel robust, nonlinear finite-time controller for the robust stabilization of the chaotic finance model. It provides an in-depth analysis based on the Lyapunov stability theory and computer simulation results to verify the robust convergence of the state variables to the origin. [ABSTRACT FROM AUTHOR]

• As far as the authors know, this paper propose the first state transformation - based state constrained intelligent control structure for a class of SUS. • In the meantime of guaranteeing the time-varying constraints, the Moreover, the unavoidable actuator failures and the dead-zone nonlinearities of the SUS can also be handled. • By using the BLS and the state transformation technique, the control design complexity can be reduced and the control response speed can be improved. In this paper, a Broad Learning System (BLS) based adaptive full state constrained controller is investigated for a class of Space Unmanned Systems (SUSs) subjected to the actuator faults and input nonlinearities. In order to guarantee the time-varying state constraints and reduce the control complexity simultaneously, two nonlinear error transformations are utilized in this work. By estimating the lower boundary of the nonlinear actuator effectiveness, the instable dynamic caused by the actuator faults and input nonlinearities can be overcome. With the aid of the universal approximation ability of the BLS, the unknown nonlinear terms existing in the SUS attitude dynamic model can be handled. Furthermore, benefiting from the nodes dynamic adjusting mechanism of BLS, the control response speed and accuracy can be improved. The simulation results are presented to demonstrate the effectiveness and advantages of the proposed BLS-based adaptive full state constrained control method. [ABSTRACT FROM AUTHOR]

This paper presents the observer-based control methodology for the one-sided Lipschitz (OSL) nonlinear systems over measurement delays. A controller design method, based on the estimated states, has been provided by applying the Lyapunov-Krasovskii functional for the delayed dynamics and by inserting the OSL constraint and quadratic inner-boundedness condition. The stability of the resultant delayed dynamics is achieved through the delay-range-dependent approach, and derivative of Lyapunov functional is exploited through the Wirtinger's integral inequality approach to reduce the conservatism of the conventional Jensen's inequality scheme. Further, a necessary and sufficient solution for the main design method has been provided by employing a tedious decoupling technique to render the observer and controller gains, simultaneously, by using the recursive optimization tools. Furthermore, the solution of matrix inequality-oriented results is handled via the cone complementary linearization technique to validate the controller and observer gains through convex optimization. The effectiveness of the resultant observer-oriented control formulation for the OSL nonlinear systems under measurement delays is validated via numerical simulation examples. [ABSTRACT FROM AUTHOR]

The PID controller is an elegant and versatile controller for set point tracking for a double integrator system, in particular, for engineering systems evolving on a Euclidean space. However, the configuration space of many mechanical systems, including interconnected ones, is a Lie group. Geometric PID control design has been proposed for mechanical systems evolving on Lie groups. In this work, we build upon this previously established framework for unconstrained mechanical systems to address systems with nonholonomic constraints. This extension encompasses many frequently encountered applications in robotics, where the constraints could either be holonomic or nonholonomic. [ABSTRACT FROM AUTHOR]

This paper presents the development of controllers to automatically align an underwater snake robot (USR) with a wake that forms behind a bluff body, while swimming at a desired distance to the object. The low-level controllers stabilize the joint motion of the USR to a swimming gait while achieving a desired orientation and tangential velocity. The high-level controllers are designed to select references for the orientation and tangential velocity to achieve a desired placement and alignment. The control system is analyzed and proven uniformly practically asymptotically stable (UPAS). The proposed control method is validated through high-fidelity simulations that capture the intricate interaction between the USR and the surrounding fluid, and is seen to perform well in these simulations. [ABSTRACT FROM AUTHOR]

This study examines new control strategies for floating offshore wind turbines (FOWTs) equipped with permanent magnet synchronous generators (PMSG), and operating in Region 2. The aim is to maximize power production while minimizing fatigue loads within wind speed limits. This is achieved by maintaining optimal tip speed ratio (TSR) using diverse control strategies. Control design based on the OpenFAST model is not trivial due to FOWTs' dynamics. Adaptive gain versions of super-twisting (STW) control methods are proposed to address this, requiring minimal system knowledge while simplifying controller gains tuning. These controllers also adapt to parameter changes, ensuring robustness. A comparative analysis of STW-based control versus baseline control demonstrates its effectiveness in maximizing power production under numerous different conditions. • Development of adaptive STW-based control laws for a 5 MW NREL OC3-Hywind FOWT. • The control strategy is develped under uncertain parameters and limited dynamic model knowledge in Region 2. • Comparative study is provided to evaluate STW-based control strategies under realistic conditions. [ABSTRACT FROM AUTHOR]