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The Anti–lock Braking System (ABS) is an active safety feature that reduces braking distance in automobiles by preventing the wheels from locking and skidding. Achieving optimal braking conditions is challenging due to the nonlinear dynamics and parametric uncertainties present in both the longitudinal dynamics of the vehicle and the wheel dynamics. To address this issue, this paper proposes a nonlinear robust controller that, using an estimator designed with High Order Sliding Mode (HOSM), estimates the parametric uncertainties and external perturbations and ensures the tracking of the desired references. The proposed controller’s performance has been validated through numerical simulations using CarSim and real–time experiments on an ABS laboratory setup, representing a quarter–car model. Quantitative results demonstrate the controller’s effectiveness, achieving reductions in key performance indicators (KPIs), such as the Mean Squared Error (MSE) of the slip tracking error and the Mean Absolute Error (MAE), compared to a baseline controller without the HOSM estimator. Additionally, the controller ensures finite–time estimation of uncertain parameters and external disturbances, enabling faster and more efficient braking. These results highlight the practical potential of the proposed methodology in enhancing automotive braking systems.

This study addresses the control problem in Electric Vehicles (EVs), specifically focusing on designing a robust dynamic control system capable of estimating parametric uncertainties and external disturbances. The EV under consideration is equipped with an Active Front Steering (AFS) system, which introduces an incremental steering angle to the front wheels. Additionally, the vehicle significantly enhances the powertrain, employing Permanent Magnet Synchronous Motors (PMSMs) mounted on the left and right wheel axle shafts. This configuration not only provides longitudinal traction but also facilitates appropriate yaw torque control, similar to the functionality of a Rear Torque Vectoring (RTV) system. This paper demonstrates how integrating the AFS system and RTV within the framework of integral control ensures that the vehicle can accurately track a predetermined trajectory, even in the presence of environmental disturbances, parametric uncertainties, or unmodeled dynamics. However, the proposed control strategy relies on precise information from the EV, particularly lateral velocity, which is challenging to measure directly in practical applications. To address this issue, a robust nonlinear observer is proposed to reconstruct the lateral velocity. Furthermore, High-Order Sliding Mode (HOSM) estimators are employed to approximate the parametric uncertainties and external perturbations in finite-time. The controller's performance is evaluated through simulations of a demanding double-step steer maneuver, conducted using Simulink software.

This paper is concerned with the attitude and position control of underactuated multirotor aerial vehicles in the presence of matched disturbances and uncertainties, using the hierarchical scheme that nests the attitude control loop inside the position one. It is well-known that the effectiveness of this scheme depends on a proper control tuning for achieving a sufficient time-scale separation (TSS) between the closed-loop (faster) rotational and (slower) translational dynamics. However, a TSS cannot be ensured under an ideal sliding mode position control law since the attitude command, computed from the position control signal, is infinitely fast. The present paper tackles this problem in a way to enforce TSS without losing robustness and using a dull trial-and-error tweak of gains. That is achieved by designing, on the one hand, a new adaptive integral sliding mode attitude control law (AISMAC) that, under a sufficient smooth attitude command, ensures the existence of an attitude sliding mode during all the time, including the adaptation phase, thus allowing an infinitely fast inner loop. On the other hand, the outer loop is equipped with a disturbance-observer-based proportional-derivative position control law that ensures the required smoothness of the attitude command and provides robustness with respect to unknown force terms. The proposed design is extensively evaluated in a realistic simulator and shows to effectively enforce the TSS.

The saturated non-singular terminal switching function (SNTSF) for sliding mode control with speed error limitation and finite-time error convergence is proposed. The sliding-mode dynamics and the boundary layer dynamics of the SNTSF are analyzed. It is also shown that the non-singular terminal switching function does not have a higher boundary layer position tracking precision than the linear switching function, contrary to some previous claims in the literature. An SNTSF sliding mode controller with speed error limitation and finite-time convergence is proposed and tested both simulatively and experimentally on a laboratory DC motor system.

This article presents a new robust formation control approach for a system of multiple Quadcopter Unmanned Aerial Vehicle (QUAV) in complex and challenging flight scenarios with large lumped uncertainties. The aim is to achieve fast convergence to the desired formation pattern, high tracking accuracy, and solid robustness. To this end, a novel finite-time nonlinear control strategy, Adaptive Backstepping Recursive Integral Non-singular Fast Terminal Sliding Mode Control (ABRINFTSMC), is designed. The formation control system of each QUAV, based on ABRINFTSMC, is divided into an underactuated position subsystem for the outer loop and a fully actuated attitude subsystem for the inner loop. A Robust Finite-Time Distributed Consensus Formation Control Protocol (RFDCFCP) is developed for the outer loop to ensure the convergence of the aircraft to the desired formation pattern in a finite time and maintain its alignment throughout the flight mission. For the inner loop, a Robust Finite-Time Attitude Stabilization Control (RFASC) is developed to allow the aircraft to track the desired attitude generated by the outer loop in a finite time. The stability of the closed-loop system is rigorously analyzed using Lyapunov theory to ensure convergence of all formation tracking errors to the origin in finite time. Finally, numerical simulations are performed under different scenarios to validate the performance of the proposed method, and a comprehensive comparative study with recent formation control approaches is carried out. The results confirm that the proposed formation control exhibits superior performance regarding fast convergence, tracking accuracy, and robustness, crucial features for multi-QUAV system flight formation.

This paper presents a streamlined two-layer control system for effective power sharing and switching control in a DC microgrid designed for electric vehicles. The system integrates Energy Storage Systems and advanced converters to ensure a broad operational range and bidirectional power flow. The Dual active bridge topology is used to integrate the EV to DC MG. Hence, the DC MG system has multiple power converter operating simultaneously. The enhanced droop control strategy is advised for the upper layer and the switching controller is derived using nonlinear controls theory embedding the barrier functions. The enhanced droop strategy shares the power considering the individual dynamics of the storage devices while Barrier-based sliding mode control is applied to converters for current/voltage tracking. Mathematical analysis, leveraging Lyapunov’s theory, confirms the large signal stability of the system. Demonstrated through MATLAB/Simulink-based simulations, the control system exhibits proficient load power sharing, and the adaptive nonlinear controller showcases robustness against unforeseen disturbances. Moreover, the comparative analysis provides insight into the performance of the proposed control methods concerning traditional methods. Hardware-in-loop tests, utilizing Typhoon HIL 404, authentically validate the real-time performance of the proposed control strategies. Different EV and Constant Power Load scenarios ensure a thorough examination, supporting the efficacy of the system. The study contributes valuable insights into the feasibility and efficiency of these control strategies, paving the way for advancements in sustainable electric mobility.

Permanent Magnet Synchronous Motor (PMSM) drives are widely used for motion control industrial applications and electrical vehicle powertrains, where they provide a good torque-to-weight ratio and a high dynamical performance. With the increasing usage of these machines, the demands on exploiting their abilities are also growing. Usual control techniques, such as field-oriented control (FOC), need some workaround to achieve the requested behavior, e.g., field-weakening, while keeping the constraints on the stator currents. Similarly, when applying the linear model predictive control, the linearization of the torque function and defined constraints lead to a loss of essential information and sub-optimal performance. That is the reason why the application of nonlinear theory is necessary. Nonlinear Model Predictive Control (NMPC) is a promising alternative to linear control methods. However, this approach has a major drawback in its computational demands. This paper presents a novel approach to the implementation of PMSMs’ NMPC. The proposed controller utilizes the native parallelism of population-based optimization methods and the supreme performance of field-programmable gate arrays to solve the nonlinear optimization problem in the time necessary for proper motor control. The paper presents the verification of the algorithm’s behavior both in simulation and laboratory experiments. The proposed controller’s behavior is compared to the standard control technique of FOC and linear MPC. The achieved results prove the superior quality of control performed by NMPC in comparison with FOC and LMPC. The controller was able to follow the Maximal Torque Per Ampere strategy without any supplementary algorithm, altogether with constraint handling.

Multi-level DC-DC converters have been widely used in automotive and other high-power applications. Thus, the control of these text multi-level converters is an emerging thematic in power electronics to ensure their proper functioning. This paper provides a novel nonlinear control of a text DC-DC three level boost converter (T-LBC) based on a backstepping (BS) technique with an integral action and is optimized using genetic algorithms (GA). Firstly, the average state model of the text T-LBC is described. Then, this model is used to design an integral BS controller; nevertheless, the controller parameters are often determined manually, which may degrade the control quality. A genetic algorithm-based optimization method is applied to establish the best controller gains and improve the proposed controller efficiency. The asymptotic stability converter is verified using the Lyapunov method criteria. In order to validate the introduced controller under different scenarios, the Matlab/Simulink environment is used. In addition, it is compared with different controllers such as conventional backstepping, fuzzy logic, and proportional–integral–derivate (PID) controllers under varying references to highlight its performance further. Finally, the designed controller is verified experimentally by implementing it using a dSPACE 1104 control board. The simulation and experimental results show that the optimized integral BS controller presents the best performances in terms of settling time, overshoot and steady-state error.

This article addresses the challenge of attitude synchronization of a group of rigid bodies (considered to be agents) with zero final angular velocity. A collaborative control strategy is proposed to tackle this issue, using decentralized consensus within a leader-follower scheme, and the communication between agents is activated by events. The attitude is parameterized by the unit quaternion. The control law incorporates an event function specifying the moment when the $i$ -th agent should transmit attitude and angular velocity information to its neighbors. The communication topology between agents is modeled using a connected and undirected graph. The event-triggered communication produces asynchronous information exchange, reducing data traffic without compromising system performance. Furthermore, in practical scenarios such as networks of satellites or aerial robots, the proposed strategy could reduce the use of communication channel bandwidth. The Lyapunov method is utilized to analyze the stability of the overall system. Numerical simulation results confirm the proposal’s effectiveness.

This paper introduces a new approach to stabilize the 6-DoF Overhead Crane by controlling its movements without requiring state measurements, using the separation principle. The movements of the system studied in this paper are described more closely than the existing crane model when considering six behaviors simultaneously: trolley and bridge movement, hoisting drum rotation, two swing angles along the $x$ -axis and $y$ -axis of the payload, and axial payload oscillation. The mission of the proposal is to make all the above behaviors of the 6-DOF crane system stable accurately enough at the desired positions and minimize both the horizontal swings of the payload and the axial oscillation of the cable by utilizing information about the position of the trolley, the bridge, and the length of cable. To guarantee these objectives, a cooperation regime controller comprising a new asymptotic state observer, which is elaborately constructed via a neural network, and the output feedback backstepping hierarchical sliding mode vehicle is integrated into the controller to improve the closed-loop system’s adaption. This cooperation controller has also evolved to prop up the fault injection data onslaught by eliminating all the information about the input system into the procedure. Furthermore, to enhance the flexibility of the closed scheme, an updating law for the observer’s parameter is developed based on the data-driven principle. All of them are developed and designed not only to handle these above tasks but also to avoid the undesired finite-escape-time (FET) phenomenon. All the results are proven systematically by three theorems and validated their performance through two scenarios and simulated by the Matlab/Simulink platform.

Single-phase grid-forming inverters are commonly used in uninterruptible power supply (UPS) systems that feed single-phase critical loads in homes, data centers, and hospitals. With the increasing use of power electronics-interfaced loads, single-phase UPS inverters are being designed to exhibit characteristics such as low total harmonic distortion (THD) in output voltage, fast dynamic response, and strong robustness against large changes in load, to ensure a seamless operation of critical loads. The Lyapunov-function-based control strategy is a popular method to provide these characteristics in UPS inverters. However, most studies and designs related to Lyapunov-function-controlled single-phase UPS inverters are conducted by using detailed switching models. While detailed switching models accurately represent the true dynamics of power converters, simulating these models with nonlinear control schemes requires small time steps to produce accurate results. To address this limitation, we propose a new model of Lyapunov-function-based single-phase grid-forming inverter using the dynamic phasor (DP) method. The DP method transforms time-domain signals into slow-varying signals, enabling the use of larger time steps in simulations, which results in shorter simulation times. In the proposed DP model, the Lyapunov energy function is constructed in the DP domain using the dominant harmonics of the inverter output voltage and output current as state variables. The high accuracy and superior computational speed of the proposed DP model are validated through comparison with results obtained from a detailed model with natural-frame-based Lyapunov-function control. Experimental test results confirm the validity and high accuracy of the proposed DP-based method of modeling Lyapunov-function-controlled single-phase grid-forming inverter.

Lower-limb exoskeletons can aid restoring mobility in people with movement disorders. Cable-driven exoskeletons can offload their actuators away from the human body to reduce the weight imposed on the user and enable precise control of joints. However, ensuring limb coordination through bidirectional motion control of joints using cables raise the technical challenge of preventing the occurrence of undesired cable slackness or counteracting forces between cables. Thus, motivation exists to develop a control design framework that integrates both a joint control loop to ensure suitable limb tracking and a cable control loop to maintain cable tension properly. In this article, a two-layer control structure consisting of high and low-level controllers are developed to ensure a knee-joint exoskeleton system follows the desired joint trajectories and adjusts the cable tension, respectively. A repetitive learning controller is designed for the high-level knee joint tracking objective motivated by the periodic nature of the desired leg swings (i.e., to achieve knee flexion and extension). Low-level robust controllers are developed for a pair of cables, each actuated by an electric motor, to track target motor trajectories composed of motor kinematics and offset angles to mitigate cable slackness. The offset angles are computed using admittance models that exploit measurements of the cable tensions as inputs. Each electric motor switches its role between tracking the knee joint trajectory (i.e., the motor acts as the leader motor to achieve flexion or extension) and implementing the low-level controller (i.e., the motor acts as the follower motor to reduce slackness). Hence, at any time, one motor is the leader and the other is the follower. A Lyapunov-based stability analysis is developed for the high-level joint controller to ensure global asymptotic tracking and the low-level follower controller to guarantee global exponential tracking. The designed controllers are implemented during leg swing experiments in six able-bodied individuals while wearing the knee joint cable-driven exoskeleton. A comparison of the results obtained in two trials with and without using the admittance model (i.e., exploiting cable tension measurements) is presented. The experimental results indicate improved knee joint tracking performance, smaller control input magnitudes, and reduced cable slackness in the trial that leveraged cable tension feedback compared to the trial that did not exploit tension feedback.

Machine-learned black-box policies are ubiquitous for nonlinear control problems. Meanwhile, crude model information is often available for these problems from, e.g., linear approximations of nonlinear dynamics. We study the problem of certifying a black-box control policy with stability using model-based advice for nonlinear control on a single trajectory. We first show a general negative result that a naive convex combination of a black-box policy and a linear model-based policy can lead to instability, even if the two policies are both stabilizing. We then propose an adaptive $\lambda$-confident policy, with a coefficient $\lambda$ indicating the confidence in a black-box policy, and prove its stability. With bounded nonlinearity, in addition, we show that the adaptive $\lambda$-confident policy achieves a bounded competitive ratio when a black-box policy is near-optimal. Finally, we propose an online learning approach to implement the adaptive $\lambda$-confident policy and verify its efficacy in case studies about the Cart-Pole problem and a real-world electric vehicle (EV) charging problem with covariate shift due to COVID-19.

An observer-based control method for high-order fully actuated systems is proposed. First, a concept of exponentially stable observers is introduced, which, different from traditional state observers, requires not only asymptotic convergence of observation errors, but also exponential convergence. Further, inspired by existing results, two design methods for exponentially stable observers are developed, one of which is less conservative and the other is simpler and more straightforward to use. Secondly, a parametric control method based on the exponentially stable observer is proposed, which ensures the exponential stability of the closed-loop system. Moreover, the proposed method does not rely on the solution of nonlinear partial differential equations, and although the system is nonlinear and time-varying, the Separation Principle still holds under this control strategy, which is a significant advantage of the proposed method. Finally, the method is applied to the attitude control of flexible spacecraft with nonlinear inertia, and comparative simulation results verify the effect of the proposed approach.

The major concern for the single-phase grid-connected inverter system is the phase and frequency error of the phase-locked loop (PLL) under various grid disturbances. This paper employs an effective cascaded band pass filter (CBPF) to eliminate the effects of the DC offset and harmonics present in the grid voltage. However, the presence of a prefilter slowed the dynamic performance of all-pass filter (APF) based PLL, implied to generate the orthogonal signal in the single-phase system. To improve the dynamic performance along with the harmonics filtering capability, a nonlinear loop filter (LF) based PLL with CBPF is proposed. The nonlinear LF contains a nonlinear function applied in proportional-integral control to improve the dynamic response of the PLL. Under various grid disturbances, the proposed controller has a faster dynamic response with less overshoot. Furthermore, the proposed PLL is capable of eliminating the effects of DC offset and subharmonics. The proposed PLL is compared with different state-of-the-art PLLs to assess the performance under various grid disturbances. The efficacy is validated experimentally as well as through simulation results. [ABSTRACT FROM AUTHOR]

This paper is concerned with the motion control for a quadrotor with a cable-suspended load (QCSL). A fixed-time control strategy is presented to improve the transient response and robustness of the QCSL with external disturbance. The overall control scheme is designed with a cascade structure to better cope with the underactuated property of the QCSL and the indirect effect of the control force on the load’s velocity through the tensile force on the cable. The simulation results are given to demonstrate the performance of the proposed scheme. Furthermore, actual flight tests were performed on a new experimental QCSL to validate the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

Resilient fuzzy stabilization is capable of providing much less conservative results than conventional fuzzy stabilization while the alert threshold condition should be always satisfied at each sampling instant. In order to make the alert threshold condition more easily to be guaranteed, the short paper employs the switching-type gain-scheduling control law so that the real-time information, which is specific to the current sampling instant, can be integrated into resilient fuzzy stabilization. More importantly, a new kind of time-variant balanced matrix is introduced for the first time for adjusting positive/negative terms of different monomials in a more flexible way. As a result, the conservatism of resilient fuzzy stabilization can be further reduced even if the alert threshold condition becomes more difficult to be violated. Finally, the advantage of the developed method is tested and validated via related comparisons on a benchmark example. [ABSTRACT FROM AUTHOR]

Controlling a quadcopter is a challenging task because of the inherent high nonlinearity of a quadcopter system. In this paper, a new quaternion based nonlinear feedback controller for attitude and altitude regulation of a quadcopter is proposed. The dynamic model of the quadcopter is derived using Newton and Euler equations. The proposed controller is established based on a feedback linearization technique to control and regulate the quadcopter. Global asymptotic stability of the designed controller is verified using Lyapunov stability criterion. A comparison of the proposed controller performance and that of the state-of-the-art quadcopter controllers is performed to ensure the effectiveness of the proposed model. The efficiency of the proposed controller is clearly shown when the quadcopter is in or near a corner pose. Simulations are performed to assess the transient and steady state performance. Steady State Error ( $E_{ss}$ ) and Max Error ( $E_{M}$ ) are used as evaluation metrics of the proposed model performance.

Unmanned aerial vehicle quadcopters have applications in different real-life areas. They are nonlinear systems that necessitate the utilization of nonlinear control techniques. In this paper, we propose a new quaternion-based tracking controller for an underactuated quadcopter based on the pseudo linear feedback linearization technique. The quadcopter dynamic model was derived using Newton and Euler equations, and the global asymptotic stability of the quadcopter was verified using the Lyapunov stability criterion. The proposed controller has been compared to three state-of-the-art quadcopter controllers. Through simulation results, it has been shown that the proposed model has an effective and better performance than others. The metrics used in this evaluation are the steady-state error, maximum error, overshoot, and settling time. The different metrics proved the good performance of the proposed model in most of the different states that are presented.

In this paper, a new model-free Model-Actor (MA) reinforcement learning controller is developed for output feedback control of a class of discrete-time systems with input saturation constraints. The proposed controller is composed of two neural networks, namely a model-network and an actor network. The model-network is utilized to predict the output of the plant when a certain control action is applied to it. The actor network is utilized to estimate the optimal control action that is required to drive the output to the desired trajectory. The main advantages of the proposed controller over the previously proposed controllers are its ability to control systems in the absence of explicit knowledge of these systems’ dynamics and its ability to start learning from scratch without any offline training. Also, it can explicitly handle the control constraints in the controller design. Comparison results with a previously published reinforcement learning output feedback controller and other controllers confirm the superiority of the proposed controller.

A continuous nonsingular terminal sliding-mode controller (N-TSMC) has been developed that ensures finite time convergence of the attitude of a multirotor subject to disturbance. A newly designed disturbance compensator is incorporated in the developed controller to guarantee that the disturbance compensation error exhibits finite-time convergence. A stability analysis showed that the developed controller can ensure that the closed-loop system achieves homogeneous finitetime stability. Simulations were performed to verify the efficacy of the developed controller. Compared with the traditional NTSMC, the simulation results indicate that the continuous NTSMC can still achieve finite-time convergence without causing high-frequency chattering since the control input is continuous. To the best of our knowledge, this is the first time that a continuous N-TSMC has been applied to multirotor systems to ensure finite-time stability.

Lane keeping control technology can improve driving safety. But the direct control torque, caused by four in-wheel motors of an electric vehicle driven by four in-wheel motors (EV-DFIM), will affect the vehicle lateral stability. For solving this issue, a two-degree-of-freedom (2DOF) lateral dynamic model of an EV-DFIM lane keeping system is constructed to obtain the lateral stability control state equations. Then a homogeneous domination-based state observer and output feedback controller are designed to improve the vehicle lateral stability and balance when the lane keeping system is working. The Lyapunov method is used to prove that the designed homogeneous domination-based output feedback controller can globally asymptotically stabilize the system. Then, a direct yaw moment strategy is presented based on the optimal allocation algorithm with the lowest utilization rate of the tire to allocate the desired torques for every in-wheel motor. Finally, numerical simulation and HIL simulation are carried out to verify that the proposed lateral stability control method based on homogeneous domination theory for the EV-DFIM lane keeping system has a good control effect and robustness.

We consider second order nonlinear systems in control canonical form, where the functional relation between the control variable and the system acceleration is nonlinear, uncertain and discontinuous. We approximate the nonlinear uncertain and discontinuous function with an invertible one, and use variable structure control theory to suppress the error of the approximate inverse. We rewrite the finite time reaching law or the terminal reaching law into the form of inequalities and use these inequalities to design a control law that drives the system state to the sliding surface in finite time, and one that ensures the convergence of the system speed and position errors to a narrow, adjustable width band around zero. The stability of the control system is also analyzed and proven. We demonstrate how to ensure the sufficiency of the available control effort, by the proper design of control parameters. The method is then validated on a numerical model of a nonlinear system with nonlinear, uncertain and discontinuous input function.

This article researches the control of triangular tethered satellite formation (TTSF) system and nonlinear state observer (NSO) design when velocity vector is unmeasured. First, the stability around the equilibrium of open-loop system is discussed, which is stable around certain equilibrium pairs. To improve the system performance, linear feedback control is designed using Jacobian matrix of original nonlinear system, which is locally stable around linearized point. Besides, nonlinear control is designed subsequently which owns global stability domain. Then in case of the unmeasured velocity states, NSO is designed which contains a nonlinear function of estimation error to regulate the observation bias. With the designed nonlinear control and NSO, the simulation of the deployment of TTSF is made thereafter. Compared with linear feedback control and general observer with linear regulation, the proposed nonlinear control together with NSO has global stability domain and less chattering, which is promising in practical application. [ABSTRACT FROM AUTHOR]

Grid-forming (GFM) inverters are dc–ac converters that regulate their ac terminal voltage and frequency in response to real-time measurements. Recent developments on GFM controls have focused on a particular dispatchable virtual oscillator control whose implementation features a nonlinear Andronov–Hopf oscillator at its core. In this article, we systematically model and study this controller, its synchronization dynamics, as well as its stability. We show that system voltages and frequency are regulated in a decentralized and autonomous manner while exhibiting nonlinear droop-like behavior. Small-signal models are formulated for an individual inverter connected to an infinite voltage bus in addition to systems of interconnected GFM inverters. These models allow us to characterize dynamical stability and synchronization. Robustness is shown after sweeping key system parameters under the aforementioned models that capture system performance. Numerical simulations and experimental results validate the analytical developments. [ABSTRACT FROM AUTHOR]

This article presents an area-efficient and fast-transient capless low-dropout regulator (LDO) with satisfactory static and dynamic performance in the full load current range. Active-capacitor frequency compensation strategy with push–pull charging ability is employed to reduce on-chip compensation cap without degrading loop stability at light load and improve transient response speed simultaneously. Moreover, in order to drive this compensation capacitance, it makes use of an adaptively biased signal- and transient-current boosting error amplifier as well as transient enhancement circuit with nonlinear control to achieve high loop gain/bandwidth and slew rate. The proposed LDO is implemented in a 0.35-μm 5V-CMOS process and occupies an active chip area of 0.077 mm2. Experimental results demonstrate that it can deliver 100-mA load current at 200-mV dropout voltage (VIN = 2.7–3.3 V, Cload≤100 pF). It consumes 66-μA quiescent current at light load and can recover within 0.7 μs for load transient. The voltage spikes at the output, undergoing a maximum load current change, are controlled well below 260 mV and good line/load regulation is achieved synchronously. [ABSTRACT FROM AUTHOR]

We present a general framework for the control of a direct current (DC) microgrid with star topology (a common DC bus) consisting of renewable sources of energy, loads, and storage devices connected via step-up and step-down DC/DC converters. The control objective is guaranteeing voltage stability in the DC microgrid while delivering power to the loads and extracting energy efficiently from renewable sources. To verify grid voltage regulation among a number of devices via current sharing, we use Lyapunov-based Input-to-State Stability (ISS) analysis. We consider three control scenarios: distributed, partially distributed, and decentralized according to the amount of information available to the controllers. [ABSTRACT FROM AUTHOR]

In this article, we combine nonlinear estimation and control methods for precise bending angle control in soft pneumatic actuators driven by a pressure source and single low-cost on/off solenoid valve. First, a complete model for the soft actuator is derived, which includes both the motion and pressure dynamics. An unscented Kalman filter (UKF) is used to estimate the velocity state and filter noisy measurements from a pressure sensor and an embedded resistive flex sensor. Then, a feedback linearization approach is used with pole placement and linear quadratic regulator (LQR) controllers for bending angle control. To compensate for model uncertainties and improve reference tracking, integral action is incorporated to both controllers. The closed-loop performance of the nonlinear estimation and control approach is experimentally evaluated with a soft pneumatic network actuator. The simulation and experimental results show that the UKF provides accurate state estimation from noisy sensor measurements. The results demonstrate the effectiveness and robustness of the proposed observer-based nonlinear controllers for bending angle trajectory tracking. [ABSTRACT FROM AUTHOR]

In this technical note, free-will arbitrary time terminal sliding mode control design is proposed. With such a design, it is possible to control the time duration of sliding in the sliding phase. Under the assumption that the chosen arbitrary time is greater than the reaching phase time ($t_{r}$), it is shown that the $n^{\textrm {th}}$ order chain of integrators converges to zero within the selected arbitrary time. An algorithm is also proposed for the case when $t_{r}$ is not known to the designer. Stability analysis based on Lyapunov theory has been provided. [ABSTRACT FROM AUTHOR]

In this work, we present a novel consensus-based secondary control scheme for current sharing and voltage balancing in dc microgrids (DCmGs), composed of distributed generation units (DGUs), dynamic RLC lines, and nonlinear ZIE (constant impedance, constant current, and exponential) loads. Situated atop a primary voltage control layer, our secondary controllers have a distributed structure and utilize information exchanged over a communication network to compute necessary control actions. Besides showing that the desired objectives are always attained in steady state, we deduce sufficient conditions for the existence and uniqueness of an equilibrium point for constant power loads— $E$ loads with zero exponent. Our control design hinges only on the local parameters of the generation units, facilitating plug-and-play operations. We provide a voltage stability analysis and illustrate the performance and robustness of our designs via simulations. All results hold for arbitrary, albeit connected, mG and communication network topologies. [ABSTRACT FROM AUTHOR]

This article investigates the properties, from a nonlinear control system standpoint, of atomic force microscope (AFM) systems, whenever operated in contact mode and controlled in the vertical direction by proportional-integral control law. By modeling the AFM as a system in which a piezo-electric actuator and a cantilever mutually interact in order to produce the sample topography, ensuing distortions affecting the quality of the yielded topography measurement are naturally cast and analyzed. The proposed investigation considers distortions due to the inception of hysteresis and vibrational dynamics within the piezo-actuator or provoked by system saturation. Both hysteresis and saturation are inherently nonlinear phenomena and are modeled as such. In spite of the inherently nonlinear nature of the AFM dynamics, investigations of the contact mode case from a nonlinear standpoint are lacking within the AFM literature. As the topography yielded by the AFM completely relies on its control algorithm, to the point that the measurement itself corresponds to the control action $v(t)$ , it becomes of paramount importance to understand how $v(t)$ relates to the actual topography, and how such a relationship is affected by the aforementioned distortions. This article hence intends to contribute to the AFM literature, by providing a study in which the very meaning of the image measurement yielded by the AFM is investigated, in the light of distortions due to nonlinear phenomena. The AFM is considered to be operated in contact mode with a PI algorithm. Furthermore, as a byproduct of the derived nonlinear stability analysis, a novel, model-based algorithm for tuning the PI control gains is provided. Finally, experimental results are presented and analyzed in view of the derived theory. [ABSTRACT FROM AUTHOR]

Large scale renewable energy systems interfaced with voltage source converters (VSCs) experience several challenging issues when integrated to weak grids. One of the specific issue i.e. control loop interaction of vector-controlled VSC under high grid impedance leads to several instability mechanism ultimately resulting in unwanted tripping of the VSC unit. As a countermeasure, a unique nonlinear adaptive stabilizing control (NASC) technique has been proposed in this paper to enhance the dynamic stability of the VSC during such scenarios. A small-signal model is developed first to examine the instability mechanism of VSC connected to weak grids under abnormal operating conditions and varying set points of the power controller. The dominant modes are identified from the analysis and a stabilizing controller is developed based on adaptive dynamic surface control philosophy for enhancing its stability. The proposed controller has been proved to be uniformly ultimately bounded using Lyapunov analysis. Besides, the stabilizing mechanism of VSC is analyzed with the proposed controller by performing small-signal stability analysis of the entire system. The efficacy of the proposed control scheme is demonstrated by performing numerical simulations in MATLAB 2017a and conducting experimental validations in controller-hardware-in-the Loop (CHIL) platform. [ABSTRACT FROM AUTHOR]

Cooperative output regulation (COR) of multiagent systems having heterogeneous uncertain nonlinear dynamics is often challenging because of the complex system dynamics and the coupling among agents. This article develops an adaptive internal model-based distributed regulator such that the outputs of a network of nonlinear agents are all regulated to a reference despite external disturbances. Specifically, we consider heterogeneous agents having nonlinear strict-feedback forms, with nonidentical unknown control directions, and subject to an unknown linear exosystem. Addressing the nonlinear COR problem shows the capability and flexibility of the proposed output regulator. The simulation results of output synchronization of Lorenz systems and cooperative tracking control of multiple ships are presented to show the capability of the proposed regulator. [ABSTRACT FROM AUTHOR]

Microgrids consisting of photovoltaic (PV) power plants and wind farms have been widely accepted in power systems for reliability enhancement and power loss reduction. Microgrids are capable of providing voltage and frequency support, improving power quality, and achieving proper power-sharing. To achieve such goals and deal with the nonlinear behavior in such systems, appropriate robust control strategies are required to be adopted. This article presents a comprehensive review of robust control methods for microgrids, including AC, DC, and hybrid microgrids, with different topologies and different types of interconnection to conventional power systems based on recently published research studies. The main control objectives, along with proposed control methods, are comparatively discussed for different types of microgrids. Furthermore, several research gaps in this area related to the scalability, robustness assessment, and evaluation approach are discussed. Recommendations are made that can potentially open new research lines to enhance the effectiveness of robust controllers for AC, DC, and hybrid microgrids. [ABSTRACT FROM AUTHOR]

This article proposes a new input–output feedback linearization control (FLC) technique of linear induction motors (LIMs), taking into consideration both the dynamic end-effects and the iron losses. Starting from a previously conceived dynamic model, including the dynamic end-effects and the iron losses, all the theoretical framework of the FLC has been developed. The proposed FLC improves a previous version of FLC in accounting also the iron losses, which in LIMs with fixed-secondary sheet play a pivotal role more than in rotating induction motors (RIMs). The proposed FLC has been experimentally tested on a suitably developed test setup, and experimental comparisons between the proposed FLC, the classic field-oriented control and a previously developed FLC, not accounting for the iron losses, have been shown in variable flux working conditions. [ABSTRACT FROM AUTHOR]

This article deals with the practical implementation of implicit homogeneous controllers (IHCs) for linearized mechanical systems. The control design includes the methodology to get gains of the IHC based on the linearized approximation of the system. If the approximation error enforced by the linearization is vanishing with the state, locally measurable and bounded, the IHC can lead the state to the origin in finite-time. This IHC control allows accelerating the convergence rate of the states. A semiexplicit algorithm is provided to exert the digital implementation of the controller. The application of the bisection method estimates the controller gain ensuring the finite-time convergence of the state to the origin. A complementary analysis provides a simplified algorithm with a reduced number of computation stages but equally efficient gain estimation. The proposed IHC is applied to a rotary inverted pendulum QUBE $^{\text{{{}}}}$ Servo 2 platform of Quanser $^\text{{{{}}}}$. The obtained results for the state convergence are compared with other classical feedback controllers to validate the effectiveness of the proposed scheme. The comparative analysis of the state convergence provides evidence of the faster convergence for the state trajectory to a zone centered on the origin with a smaller hypervolume than the one gotten with the classical controllers. [ABSTRACT FROM AUTHOR]

Renewable energy sources are gradually replacing conventional synchronous generators, which are responsible for supplying the power grid inertia damping properties. This paper proposes a nonlinear optimal controller for a renewable energy generation system based on a power electronics inverter, in order to incorporate the system inertia behavior through imitating the rotor inertia of synchronous generators. The main contributions of this paper are: 1) the modeling and synthesis of a nonlinear optimal control scheme for a power inverter such that it dynamically behaves as a conventional synchronous generator, where the active and reactive power are regulated, and provides robustness against utility grid disturbances; 2) the dynamical modeling of the virtual inertia-based inverter generator and its corresponding response to power reference variations and utility grid voltage disturbances. Further, an analysis procedure is presented to compute a predefined value of the inverter inertia constant, proportional to the one that a synchronous generator could provide, but taking into account the rated power of the generator. Simulation results assess the proposed methodology effectiveness [ABSTRACT FROM AUTHOR]

We consider feedback control design for a wave energy converter (WEC) for which the power takeoff (PTO) system has a finite stroke limit. Stationary stochastic wave loading is assumed, with a known spectrum, and the plant dynamics are assumed to be linear. We develop a technique for the design of a discrete-time controller, which has three design stages. In the first stage, a linear controller is optimized while imposing a relaxation of the maximum stroke constraint on the design. In the second stage, a tandem nonlinear feedback loop is designed for the purpose of stroke protection. In the third stage, the two designs (linear and nonlinear) are fused in a manner that preserves the stability of the overall system. The technique is demonstrated in a simulation of a simple cylindrical buoy. We show that the controller may be tuned through the adjustment of scalar design parameters, which adjust the tradeoff between the mean generated power and the force levels required to protect the stroke. [ABSTRACT FROM AUTHOR]

This study designs a high-precision bilateral teleoperation control for a dissimilar master–slave system. The proposed nonlinear control design takes advantage of a novel subsystem-dynamics-based control method that allows designing of individual (decentralized) model-based controllers for the manipulators locally at the subsystem level. Very importantly, a dynamic model of the human operator is incorporated into the control of the master manipulator. The individual controllers for the dissimilar master and slave manipulators are connected in a specific communication channel for the bilateral teleoperation to function. Stability of the overall control design is rigorously guaranteed with arbitrary time delays. Novel features of this study include the completely force-sensor-less design for the teleoperation system with a solution for a uniquely introduced computational algebraic loop, a method of estimating the exogenous operating force of an operator and the use of a commercial haptic manipulator. Most importantly, we conduct experiments on a dissimilar system in two degrees of freedom (DOFs). As an illustration of the performance of the proposed system, a force scaling factor of up to 800 and position scaling factor of up to 4 was used in the experiments. The experimental results show an exceptional tracking performance, verifying the real-world performance of the proposed concept. [ABSTRACT FROM AUTHOR]

An adaptive robust controller is introduced for high-precision tracking control problems of robotic manipulators with output constraints. A nonlinear function is employed to transform the constrained control objective to new free variables that are then synthesized using a sliding-mode-like function as an indirect control mission. A robust nonlinear control signal is derived to ensure the boundedness of the main control objective without violation of physical output constraints. The control performance is improved by adopting a neural-network model with conditioned nonlinear learning laws to deal with nonlinear uncertainties and disturbances inside the system dynamics. A disturbance-observer-based control signal is additionally properly injected into the neural nonlinear system to eliminate the approximation error for achieving asymptotically tracking control accuracy. Performance of the overall control system is validated by intensive theoretical proofs and comparative simulation results.

The majority of marine current conversion technologies are based on permanent magnet synchronous generators (PMSG) due to its numerous advantages such as high-power density, low cost, and favorable electricity production. However, nonlinear properties of the generator and parameter uncertainties, makes the controller design more than a simple challenge. This paper proposes a new adaptive passivity-based (PB) modified super twisting algorithm (PBSTA) for control performance improvement (low tracing errors, fast convergence response, robustness) of a PMSG based marine current energy conversion system under swell effect and parameter uncertainties. The proposed approach combines a new PB current control (PBCC) with a new adaptive modified super twisting algorithm through a fuzzy logic supervisor. A new adaptive fractional order PID (FO-PID) controller is introduced to design the desired dynamics of the system. The main contributions and motivation of this work include the extraction of maximum power from the tidal current, integrating it to the grid and making the closed loop system passive. This is possible by reshaping system energy and introducing a damping term that compensates the nonlinear terms by a damped way and not by cancellation. Two steps are needed to design the proposed controller: the first step includes the derivation of reference current based on the reference torque using adaptive FO-PID. In the second step, the overall control law is computed by the proposed PBSTA. The exponential stability and error convergence of the proposed controller are analytically proven. The developed controller is tested under parameter variations and it is compared to benchmark nonlinear control methods such as sliding mode. Extensive investigation under MATLAB/Simulink, demonstrates clearly that the proposed technique provides higher efficiency and robustness over the benchmark nonlinear control methods.

The problem of carrying a bar-shaped payload suspended by flexible cables attached to two quadrotors is analyzed in this work. The aerial vehicles and the load are dealt with as a single system, whose kinematics is described as a multi-robot formation using the virtual structure approach. The dynamic effects caused by the tethered load over the quadrotors, as well as those caused by each quadrotor over the other, are treated by an adaptive dynamic compensator. To validate the proposal, experiments were run testing the system in adverse conditions: transportation far from quasi-static motion, high payload-to-quadrotor weight ratio, 20% of error in the robot model parameters, transportation under wind disturbances, and payload weight changes during flight. The good performance of the proposed control system in all these tests allows concluding that the proposed system is able to accomplish payload positioning, orientation, and trajectory tracking under adverse conditions, with accelerations up to 1.6 m/s2.

This paper proposes an improved back-stepping control approach and its application to small nonlinear UAV control systems with uncertainties such as external disturbance. Unlike traditional back-stepping control methods, the idea of prescribed performance function (PPF) is incorporated into the control design, such that both the transient and steady-state control performance can be strictly guaranteed. Moreover, we design a novel tracking differentiator to avoid the “differential expansion” problem well caused by the calculation of derivative. Significantly, the function approximators (e.g. neural networks) that are widely used to address the unknown nonlinearities in the nonlinear control designs are not needed. Finally, the numerical simulation verifies the convergence and robustness of the system, and the results show that the control strategy can obtain better transient and steady-state performance.

In this research, a new robust control method is developed, which achieves a fixed-time convergence, robust stabilization, and high accuracy for trajectory tracking control of uncertain magnetic levitation systems. A hybrid controller is a combination of an adaptive fixed-time disturbance observer and a fixed-time control algorithm. First, to estimate precisely the total uncertain component in fixed-time, an adaptive disturbance observer is constructed. Then, a new robust control method is designed from a proposed fixed-time sliding manifold, disturbance observer’s information, and a continuous fixed-time reaching law. A global fixed-time stability and convergence time boundary of the control system is obtained by Lyapunov criteria in which the settling time can be arbitrarily set using design parameters regardless of the system’s initial state. Finally, the designed control strategy is implemented for a magnetic levitation system and its control performance is compared with other existing finite-time control methods to evaluate outstanding features of the proposed system. Trajectory tracking experiments in MATLAB/SIMULINK environment have been performed to exhibit the effectiveness and practicability of the designed approach.

This work presents a nonlinear control strategy for a magnetically coupled multiport dc-dc converter aimed at automotive applications. First, a behavioural dynamic model, based on averaging the power flowing among the ports, is derived. Then, a control algorithm, based on feedback linearization techniques, is proposed. Essentially, the controller ensures decoupling and a linear dynamic behaviour thanks to a transformation of control and state variables, and a conventional PI action is devised to render asymptotic stability, as well as robustness to load uncertainties. The inversion of the control transformation, which involves nonlinear terms, is carried out using linear approximations with no significant performance decay. Hence, simplicity and efficiency are the main features of the control design. The proposed controller is validated via experimental results.

The main advantage of the incremental dynamics formulation is its property of replacing state-dependent aspects of the system dynamics by measurements, solely requiring modeling the input-dependent dynamics. However, incremental controllers assume that state derivative measurements are available. The lack of accurate sensors and communication delay may appear as limitations for the use of incremental techniques. This article applies a second-order differentiator (SOD) for estimating state derivatives and attenuate measurement noise, and an input scaling gain (ISG) for attenuating the effects of high-frequency noise and delay in the feedback loop. A complete analysis of the combined solution is carried out using an incremental nonlinear dynamic inversion (INDI) strategy. First, a simple linear single-input single-output model is used to evaluate the influence of design parameters in the closed-loop response and stability. Then, the combined SOD and ISG approach is illustrated in a more complex case application, where INDI is used to control the lateral motion of an autonomous airship, results of which corroborate the ISG as an asset to increase the maximum delay allowed in the feedback loop. [ABSTRACT FROM AUTHOR]

In this article, a reinforcement learning (RL)-based controller is proposed for a multirotor-based transportation system, guaranteeing that the trained RL controller is effective in both simulation and practical experiments. The main novelty lies in that, as far as we know, this is the first attempt of combining the advantages of nonlinear and intelligent control techniques to derive a practice-oriented RL controller for the multirotor-based transportation system, where the high-dimensional complicated dynamics are fully considered in the framework. Specifically, inspired by the physical insight of the system, a new nonlinear control approach is proposed, in which the underactuated properties and the nontrivial couplings are well handled. On this basis, an RL network is proposed to parameterize the nonlinear controller, where the obtained algorithm presents the features of strong reliability and fast convergence even in complicated working conditions (e.g., model uncertainties, parameters drift, external disturbances, and so on). Subsequently, the states are proven to asymptotically converge to the equilibrium point by Lyapunov analysis and RL techniques. A series of simulation and real world experiments are implemented to verify satisfactory positioning accuracy and robustness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

For individuals with neuromuscular disorders (NDs) affecting the coordination and control of their legs, motorized functional electrical stimulation (FES) cycling serves as a rehabilitation strategy and offers numerous health benefits. A motorized FES cycle is an example of a hybrid exoskeleton involving cooperative physical human–robot interaction where both the cycle’s motor and rider’s muscles (through electrical stimulation) must be controlled to achieve desirable performance. A robust sliding-mode cadence controller is developed for the rider’s muscles, while an adaptive admittance controller is employed on the cycle’s motor to preserve rider comfort and safety. A switched systems stability analysis using Lyapunov and passivity-based methods is conducted to ensure global asymptotic stability of the admittance error system and that the cadence error system remains passive. Experiments are conducted on one able-bodied participant and four participants with NDs to illustrate the performance of the control design. For the participants with NDs, the controller achieved an average admittance tracking error of −0.08±1.05 rpm at an average cadence of 47.85±1.13 rpm for the desired cadence of 50 rpm. [ABSTRACT FROM AUTHOR]

Modular multilevel converter (MMC) is an attractive topology in industrial applications such as high-voltage direct current (HVdc) transmission system where fast power control is required. The most conventional control method for MMC uses cascaded structures, where the power transmission and internal energy dynamic (outer loops) is limited by the “frequency separation” constraints since the dynamic choice of the currents (inner loops) must consider the tradeoff between rapidity and robustness. In this article, we present a new control method based on a differential flatness theory. The main interest of the proposed control is the possibility to obtain a very high dynamic performance of the MMC power flow, even under noisy measurements and parametric disturbances. Using the well-known average model of the MMC, a flat output is proposed, proving the differential flatness property of the MMC. Trajectory tracking controllers of ac grid active and reactive power are proposed using input-state full-order linearization. Simulation results, including losses corresponding to a realistic case of on-shore, point-to-point HVdc interconnection, are presented to show the performance of the proposed control scheme even with strong measurement noise. [ABSTRACT FROM AUTHOR]