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This paper proposes an improved two‐degree‐of‐freedom active disturbance rejection controller for the coupling problem of asynchronous motor vector system. To simplify the analysis process and accommodate observers of different types, a unified expression based on different controllers for the system output is developed. The closed‐loop transfer function generated by the reference input and load disturbance is given. For the coupling problem of motor output speed and immunity, the structure of a higher‐order extended state observer is reconstructed. The extended state observer estimates both the output speed and the total system disturbance, which serve as feedback and feed‐forward compensation quantities. Compared to the PI controller and traditional active disturbance rejection controller, the proposed controller achieves decoupling of output response speed and immunity, simplifies the process of parameter tuning. Finally, simulation and experiment results verify the feasibility and effectiveness of the algorithm in this paper. [ABSTRACT FROM AUTHOR]

The concurrent existence of model uncertainties, external disturbances, and actuator faults in a nonlinear system such as a robotic manipulator can significantly affect the trajectory tracking performance of these systems. Therefore this study is devoted to proposing a control approach based on fixed‐time control theory to improve the trajectory tracking performance of the robotic manipulator in the presence of lumped disturbance, including uncertainties, external disturbances, and actuator faults. The control approach in this paper is designed based on the integration of a fixed‐time adaptive sliding mode observer and a fixed‐time non‐singular fast terminal sliding mode control design strategy. Firstly, a new fixed‐time adaptive sliding mode observer is designed based on fixed‐time theory and adaptive control theory to estimate the lumped disturbance present in the system. Then, using the information from the disturbance observer, the fixed‐time non‐singular fast terminal sliding mode control is devised based on a non‐singular fixed‐time sliding surface and a fixed‐time reaching approach. Furthermore, in the sense of the Lyapunov theorem, through rigorous analysis, it is demonstrated that the tracking errors of the closed‐loop system converge to a small neighbourhood within a fixed time, regardless of the information about the initial conditions of the states of the system. Finally, extensive comparative simulations are performed using the PUMA560 robot to manifest the feasibility and validity of the proposed control strategy in terms of trajectory tracking accuracy and fast convergence in the presence of uncertainties, disturbances, and actuator faults. [ABSTRACT FROM AUTHOR]

This paper proposes a nonlinear control law with a dynamic controller based on high gain observer (HGO) for a co‐axial double rotor magnetic gear (CADRMG) based on Halbach array used in wind turbines. The generalized canonical form (GCF) is used to normalize the nonlinear augmented system to achieve the dynamic control signal with a chain of integrator of system output. In addition, a tracking problem is defined to track high speed rotor (HSR) with respect to GCF. On the other hand, the HGO is used to estimate the error tracking at the expense of nonlinear terms. Furthermore, the nonlinear system observability of the augmented system is evaluated. A dynamic control law is used to solve the tracking problem based on HGO. This controller can eliminate the effect of load torque as a constant and unknown disturbance in the closed‐loop system. Moreover, the closed‐loop stability of the system under dynamic signal control is guaranteed. The system states estimation is calculated by recursive equations from tracking error estimations. Finally, numerical simulations are given to illustrate the theoretical results of proposed system. [ABSTRACT FROM AUTHOR]

Point‐to‐point control of underactuated mechanical systems is a challenging problem, especially if some of the system's parameters are uncertain. A popular method to stabilize underactuated manipulators is total energy shaping, in which a new Hamiltonian function is assigned to the closed‐loop system while a set of partial differential equations (PDEs) should be solved. In this study, an adaptive total energy shaping controller based on the approach called interconnection and damping assignment passivity‐based control (IDA‐PBC) for some underactuated robots is designed. The proposed method can overcome uncertainties in the dynamical parameters and also the parameters of the input mapping matrix under the satisfaction of the PDEs. The stability of the desired pose is ensured by the Lyapunov approach via suitable design of adaptation laws without the requirement for the persistence of excitation condition or other similar conditions. The results are applied to a 3‐DOF underactuated manipulator and verified by simulations. [ABSTRACT FROM AUTHOR]

This paper proposes explicit solutions for the algebraic Riccati matrix equation. For single‐input systems in controllable canonical form, the explicit Hermitian solutions of the non‐homogeneous Riccati equation are obtained using the entries of the system matrix, the closed‐loop system matrix, and the weighting matrix. The unknown entries of the closed‐loop system matrix are solved by scalar quadratic equations. For a homogeneous Riccati equation with a zero weighting matrix, the explicit solutions are proposed analytically in terms of the system eigenvalues. The advantages of the explicit solutions are threefold: first, if the system is controllable, the solution is directly given and the invariant subspaces of the Hamiltonian matrix are not required; second, if the system is near singularity, the explicit solution has higher numerical precision compared with the solution computed by numerical algorithms; third, for a real system in the controllable canonical form, the non‐negativity can be analysed for the explicit almost stabilizing solution. [ABSTRACT FROM AUTHOR]

This study presents a systematic methodology for developing a stabilizing controller for a general hybrid systems model. The approach is based on utilizing the small‐gain theorem as a means of constructing the Lyapunov function and analyzing the input–output stability of the subsystems in the feedback loop. By considering the control system in a closed‐loop configuration with the hybrid system, the small‐gain theorem can be applied. In this scheme, a dynamic control system is proposed that satisfies the closed‐loop stability conditions. This method applies to various hybrid systems' applications due to its generality. To demonstrate the effectiveness and performance of the proposed control approach, two simulation examples, including a linear hybrid system and a bipedal walking robot, are examined. [ABSTRACT FROM AUTHOR]

To reduce the learning time and space occupation, this study presents a novel model‐free algorithm for obtaining the Nash equilibrium solution of continuous‐time nonlinear non‐zero‐sum games. Based on the integral reinforcement learning method, a new integral HJ equation that can quickly and cooperatively determine the Nash equilibrium strategies of all players is proposed. By leveraging the neural network approximation and gradient descent method, simultaneous continuous‐time adaptive tuning laws are provided for both critic and actor neural network weights. These laws facilitate the estimation of the optimal value function and optimal policy without requiring knowledge or identification of the system's dynamics. The closed‐loop system stability and convergence of weights are guaranteed through the Lyapunov analysis. Additionally, the algorithm is enhanced to reduce the number of auxiliary NNs used in the critic. The simulation results for a two‐player non‐zero‐sum game validate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper addresses the tracking control for an extended chained nonholonomic system under input saturation and matched disturbances. Specifically, the tracking error dynamic system is split into two subsystems in a cascade form. An integral sliding mode saturated controller is designed in combination with a finite‐time observer (FTDO) to ensure the finite‐time stability of the first subsystem, thereby simplifying the design of the second subsystem. A backstepping‐based adaptive saturated tracking control method is proposed for the second subsystem by incorporating the filter technology. The stability of the resulting closed‐loop system is demonstrated, and the tracking errors can be arbitrarily minimized through the appropriate design parameter selection. The effectiveness of the proposed scheme is validated through simulation and experimental results. [ABSTRACT FROM AUTHOR]

This article proposes an online solution to address the problem of closed‐loop system identification using multiple recursive least squares estimation protocols. Some control systems cannot be analysed in an open‐loop form for stability reasons or the requirement for online control system operation. So, it is necessary to identify plant dynamics and controller parameters based on input–output data from the feedback structure. The presented method identifies real‐time parameters of plant dynamics and controller parameters by utilising a series of recursive least square estimation algorithms that estimate open‐loop data from noisy input–output data measured from the closed‐loop feedback structure. The proposed method can effectively identify abrupt variations in both the controller parameters and plant dynamics. This capability makes it valuable for deployment as a supervisory component, enabling the detection of any faults that may arise in operating systems. Mathematical formulations and theorems are developed, and two numerical case studies are presented to examine the feasibility and performance of the presented closed‐loop system identification protocol. [ABSTRACT FROM AUTHOR]

This paper concentrates on presenting a reliable procedure to compute the stabilizing region of fractional‐order proportional integral derivative (FOPID) controllers for interval fractional‐order plants having an interval time delay. An interval fractional‐order plant is defined as a fractional‐order transfer function whose denominator and numerator coefficients are all uncertain and lie in specified intervals. Also, an interval time delay points to a delay term whose value varies in a specific interval. The D‐decomposition technique and the value set concept are employed to determine the stabilizing region of FOPID controllers. In this study, first, a theorem is presented to compute the boundary of the value sets of systems having interval time day. Then, a lemma is provided for robust stability analysis of the given closed‐loop control system. For a convenient use of the paper results, an algorithm is proposed to solve the problem of robustly stabilizing interval fractional‐order plants with an interval time delay using FOPID controllers. Finally, four examples are provided to illustrate the proposed procedure. [ABSTRACT FROM AUTHOR]

This paper proposes a Modified model reference adaptive controller and observer (MMRACO) for unknown linear time‐invariant (LTI) systems. The recent literature, and in particular the so‐called MRACO approach, has demonstrated how some deficiencies in standard model reference adaptive control can be overcome by using a combination of modified reference models and observers, but this is done at the expense of knowing bounds on certain unknown parameters. Here, a novel adaptive observer/controller combination is presented which removes the need to know the above bounds but preserves the other desirable features of the MRACO approach. A Lyapunov analysis of the closed‐loop system ensures asymptotic convergence of both tracking and observer errors, with uniform boundedness of parameter estimation errors. A key advantage of the scheme is that the design involves only solutions of two Lyapunov equations (or linear matrix inequalities) and does not require the selection of a "high gain" parameter. The effectiveness of the approach is illustrated in some numerical examples. [ABSTRACT FROM AUTHOR]

The development of an autotuning mechanism for robotic manipulators, inspired by the success of autotuners in industrial systems, aims to reduce the time and cost of tuning robotic manipulators. This paper introduces an auto‐tuning method for PID controllers in robotic manipulators using the Modified Relay Feedback Test (MRFT) and the Optimization Under Uncertainty (OUU) principle. The mechanism is versatile, suitable for manipulators of varying scales and motor power capacities. It incorporates actuator dynamics and a combined model of Brushless DC motors with an n‐link manipulator for TR development. Various manipulator models, including commercial and open‐source types were used to refine and test the TR. An algorithm is also proposed for tuning commercial manipulators' controllers without changing the existing closed‐loop system structure. Experimental and simulation tests demonstrate the method's effectiveness, showing better performance than traditional approaches, particularly in reducing overshoot and settling time. [ABSTRACT FROM AUTHOR]

Electrostatic micro electro mechanical system (MEMS) as an actuator is one of the most widely used actuators in micro dimension systems. Due to the high nonlinear characteristics in the micro actuator's model, nanopositioning has been a challenging problem for researchers. In addition, the system is subject to uncertainties associated with the system's unknown parameters and un‐modelled dynamics. Thus, to overcome these problems and achieve precise positioning a robust non‐linear control method is required. In this research, an optimal voltage control algorithm is initially designed utilizing the nonlinear predictive control approach. The Taylor expansion sequence is used to estimate the final position of the parallel plate actuator. To approximate unknown disturbances, a radial basis function neural network (RBFNN) has been designed. The estimations made were used in updating the control input in the previous step, and the obtained results showed an increase in the robustness of the designed controller. The stability of the closed‐loop system is also analyzed. Finally, a comparison is accomplished between the potential of the proposed controller and that of the feedback linearization and sliding mode controllers. The obtained results indicate better performance and robustness of the suggested controller. [ABSTRACT FROM AUTHOR]

This paper presents a new fuzzy non‐singular fast terminal decoupled sliding mode control based on the finite‐time extended state observer for trajectory tracking control of flexible joint robot manipulators under chaos and uncertainty. First, a suitable chaotic reference is used in a synchronization mechanism to create chaos in the dynamics. Then, the essential modifications made to the conventional decoupled sliding mode control are introduced. A new coupling variable and a non‐singular fast terminal sliding surface are proposed in combination with an extended state observer. A complete convergence analysis is also performed for all the sliding surfaces. Furthermore, two fuzzy systems are designed in such a way that not only they can eliminate the chattering phenomenon but can also improve the convergence time without increasing the control input in a voltage‐based manner. The mathematical proof guarantees the finite‐time asymptotic stability of the closed‐loop control system under the proposed scheme for a class of under‐actuated systems in the presence of structured and un‐structured uncertainties. Finally, some simulations and experimental implementations as hardware‐in‐the‐loop are performed to evaluate the proposed method's performance. The proposed controller is an effective method, as confirmed by the numerical simulation results and experimental validation. [ABSTRACT FROM AUTHOR]

This paper investigates the robust model reference tracking control problem for high‐order descriptor linear systems (HODLS) subject to norm‐bounded parameter uncertainties. The problem is divided into two subproblems: a robust proportional plus derivative state feedback stabilization (RPPDSFS) problem and a robust feed‐forward compensation (RFFC) problem. In the presence of uncertainties, by using the controller consisting of RPPDSFS part and RFFC part, all the signals of the closed‐loop system are bounded. The latter is equivalent to seeking three coefficient matrices such that a series of linear matrix equations are satisfied, and simultaneously the effect caused by uncertainties is minimized. Based on the right coprime factorization, the RFFC problem is further converted into a minimization problem with a quadratic performance index and some linear constraints. Thereafter, a linear matrix equation that determines the optimal solution is achieved. The restrictive condition that the coefficient matrix of the augmented reference system is non‐defective is relaxed, which reduces the conservativeness. A numerical example and the application of a three‐axis dynamic flight motion simulator manifest the effectiveness and the practicability of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The paper expounds the question of echo state network‐based fixed‐time adaptive tracking control for a type of multi‐input multi‐output nonlinear strict‐feedback system with input delayed saturation. Based on the feature that echo state network can obtain better estimation performance at lower computational cost, it is utilized to approximate the unknown nonlinear function in the controller design course. By constructing an auxiliary system, a time‐delay system with input saturation is eliminated. Moreover, command filtering techniques can be applied to avoid the "complexity explosion" problem in the backstepping method. Then, the closed‐loop system is attested to be semi‐global practical fixed‐time stable. In the end, a simulation shows the valid scheme. [ABSTRACT FROM AUTHOR]

This paper concentrates on network congestion and security issue for networked control systems under the hybrid attacks. The hybrid attacks including deception attack, replay attack and denial‐of‐service attack are modelled as Bernoulli random process. A general form adaptive event‐triggered scheme (AETS) under the hybrid attacks is designed to alleviate the network congestion and save communication resources utilizing adaptive threshold and the weighted average of data packets. Meanwhile, the security issue under the hybrid attacks is addressed by a dynamic output feedback controller (DOFC) based on the AETS. Moreover, the sufficient conditions are obtained by a piecewise Lyapunov function to guarantee that the closed‐loop system is exponentially mean‐square stable. A practical experiment on networked motor control system verifies the effectiveness of the proposed scheme. The proposed scheme can not only save communication resources to further alleviate network congestion, but also defense the hybrid attacks in the network. [ABSTRACT FROM AUTHOR]

The growth of marine resources exploitation has led to increased research interest in electro‐hydraulic systems for marine simulation. This study proposes a proportional plus resonant (PR) controller to achieve high tracking performance for electro‐hydraulic systems. Due to the complex structure and non‐linear flow dynamics, establishing accurate mathematical models of electro‐hydraulic systems is challenging. The local linearization technique is applied to simplify the process of model establishment. The system gain is limited by the stability margin due to the input delay, resulting in a phase delay between the real trajectory and the desired reference. To compensate for the phase delay in tracking periodic reference with the traditional proportional and integral controller, a resonant item is added into the controller. The stability analysis of the closed‐loop system is performed using Routh‐Hurwitz criterion. Furthermore, the controller parameters are tuned based on the frequency characteristic to achieve high tracking performance and maintain the adequate stability margin. The effectiveness of the proposed PR controller in tracking periodic references is validated through numerical simulations and practical experiments. [ABSTRACT FROM AUTHOR]

Here, an adaptive radial basis function (RBF) neural network (NN) backstepping controller is proposed for a class of input‐constrained flexible joint robotic manipulators represented by strict‐feedback form with unknown terms, external stochastic disturbance, and output disturbance. The proposed approach is robust against both deterministic and stochastic uncertainties and disturbances and copes with the control input amplitude saturation. Moreover, by deploying the minimal learning parameter method and command filter technique, the computational burden of derivative terms and adaptive terms greatly decreases. Considering the mean‐value theorem assists us to avoid the need for having the input saturation bounds in prior. The suggested tracking control scheme mandates the closed‐loop system states to be semi‐globally bounded‐in‐probability. Also, a quartic Barrier Lyapunov function is utilized to force the tracking error to be confined within a pre‐chosen small region around the origin. Eventually, a numerical simulation of a flexible joint robot manipulator with a single link is performed to show the effectiveness and performance of the developed control method. [ABSTRACT FROM AUTHOR]

A robust tube‐based distributed model predictive control method is proposed for spatially interconnected systems with constraints and disturbances. The system contains multiple discrete‐time piecewise affine subsystems, which are coupled to each other through states. The predictive states of each subsystem are dependent on its states, inputs, and neighbouring states, and shrinking constraints are constructed to deal with the disturbances and the model mismatches. The differences between the predicted states at the current time instant and the optimal states at the previous time instant are constrained, which improves the accuracy of the predicted model and enhances the control performance. The conditions which ensure the recursive feasibility of optimization problems and the asymptotic stability of closed‐loop system are obtained. The effectiveness of the proposed method is verified by the simulation results. [ABSTRACT FROM AUTHOR]

The issue of constrained output feedback receding horizon control (RHC) for Takagi‐Sugeno systems is studied in this paper. The control strategy is developed through parameterizing the infinite horizon control moves as a non‐parallel distributed compensation (non‐PDC) law. The parameter‐dependent non‐PDC controller is optimized in a receding horizon manner. The extended non‐quadratic Lyapunov function serves to guarantee the robust stability of the augmented closed‐loop system, which is an improvement over existing results with common‐quadratic Lyapunov functions. The recursive feasibility of the proposed approach is also carefully analyzed. The approach is shown to enhance the control performance at a cost of computational efficiency. A numerical example is demonstrate the effectiveness of the approach. [ABSTRACT FROM AUTHOR]

This article investigates practical tracking joint with obstacle‐avoidance for a class of uncertain robotic systems. The remarkable features are revealed from two aspects. First, more serious system uncertainties are allowed than the related literature due to the presence of unknown system matrices and mismatched disturbance in the investigated system. Second, only coarse conditions are required on reference trajectory and obstacles since their time derivatives are not necessarily to be available for feedback but those of the related literature muse be, while the reference trajectory is only required to be first rather than second order continuously differentiable. For this, a secure adaptive control framework is established by incorporating adaptive dynamic compensation mechanism into the backstepping procedure with the smart choice of adaptive law and the skillful injection of a barrier function. Consequently, a state‐feedback controller is explicitly designed which guarantees the obstacle‐avoidance of the robotic system while all the signals of the resulting closed‐loop system are bounded with system output practically tracking the reference trajectory. Finally, simulation results are provided for two specified robot systems to validate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper proposes a tube‐based robust model predictive control (TMPC) scheme with an optimal tube for disturbance‐affected linear systems. In the literature on TMPC, there is no proper methodology to handle the considerable effects of the tube size on the closed‐loop system performance. There is usually a trade‐off between the disturbance rejection level and the amount of control effort available for the MPC problem. In some applications, it is nearly impossible to find a feasible TMPC to have a sufficient amount of states and inputs feasible sets for the MPC optimization problem. It would be a vital contribution to the TMPC designs if an algorithm is demonstrated which can investigate the suitability of TMPC for a specific system. This paper provides a solution for the mentioned challenges by introducing the concept of Quasi‐H∞ criterion and proposing a constrained optimization problem. The optimization problem is then reformulated and simplified to present an efficient methodology for the TMPC designers. The proposed TMPC scheme could benefit from a larger terminal region and result in a larger region of attraction. The achievements in TMPC designs are shown by simulations and comparisons with the previously used techniquesover numerical case studies. [ABSTRACT FROM AUTHOR]

This article investigates the finite‐time tracking control problem for disturbed non‐holonomic systems with input saturation and state constraints. Input saturation is ensured by utilizing saturated state feedback and designing auxiliary variables. A rigorous design procedure, which combines barrier Lyapunov function‐based backstepping and neural networks, is introduced to satisfy state constraints and overcome the influence of lumped disturbances. A finite‐time filter is developed to address the explosion of complexity problem. Together with relay switching, the designed saturated controller guarantees that the tracking errors converge to arbitrarily small neighbourhoods around zero within a finite time. Stability analysis indicates that all closed‐loop system signals maintain bounded, and the desired input and state constraints are not violated throughout the control process. To demonstrate the effectiveness of the proposed approach, simulation and experimental results on a wheeled mobile robot are presented. [ABSTRACT FROM AUTHOR]

This work proposes the framework of dual dynamic triggers to deal with the communication problem of remote control under the event‐triggered scheme for network control systems (NCSs). Compared with the existing NCSs, a local controller is set up at the plant site, which provides the local control input for the plant as a remote controller. The remote controller and the plant measurement have their individual dynamic triggers. Thus it is allowed that the local controller and the remote controller permit asynchronous communication, which is governed by different event conditions. It is proven that the proposed control strategy can drive the closed‐loop system asymptotically to equilibrium. Finally, a numerical example is presented to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptive observer‐based scheme to control fractional‐order chaotic micro‐electro‐mechanical‐systems (MEMS). The fractional‐order model of a system exhibits the dynamic behaviour of a physical system more accurately than a similar integer‐order one. An observer‐based control considering the unknown parameters is presented for a fractional‐order chaotic micro‐electro‐mechanical‐system. To handle the existence of the unknown parameters, the control law consists of both estimated parameters and also estimated states that have been designed. First, a fractional‐order observer is designed to estimate the state variables. The asymptotic convergence to zero of the estimation state error is proved using the Lyapunov scheme. After that, with the designed observer as a foundation, adaptive control is expanded for the closed‐loop system to ensure its asymptotic stability. An evaluation of the proposed method shows its efficacy via simulations for two case studies. [ABSTRACT FROM AUTHOR]

This paper presents a command‐filter‐based formation control scheme for the leader‐follower omnidirectional mobile robots (OMRs) subject to the absence of the velocity measurements, input saturation and unknown bounded disturbances. First, an adaptive velocity observer is designed based on a novel state transformation of the OMR dynamics. Then, a finite‐time command filtering strategy is proposed, where the Levant filter is used to estimate the time derivative of the virtual control law, and an error compensator with finite time convergence is constructed to eliminate the filtering error correspondingly. Moreover, the anti‐saturation module and adaptive law are designed to attenuate the influence caused by input saturation and external disturbances. The proposed control scheme can ensure that all signals of the closed‐loop system including the formation error are uniformly bounded, and the effectiveness is verified by the simulations results. [ABSTRACT FROM AUTHOR]

Global sampled‐data stabilization for a class of nonlinear continuous system with input delay has been investigated directly in the discrete‐time domain due to challenges confronted in dealing with infinite‐dimensional system under input delay. Memorized state feedback controllers and output feedback controllers based on dynamic extension of state space have been constructed within the framework of co‐design between sampling period and scaling gain. Upon this compensation scheme, global sampled‐data stabilization a class of nonlinear system has been successfully realized no matter the input delay is smaller than the sampling period or not. Compared with memory‐less sampled‐data controllers, not only sampled‐data stabilization under large input delay has been realized but also transient performance of closed‐loop system has been further improved. Simulation results under different input delays and sampling periods have illustrated the effectiveness of results obtained. [ABSTRACT FROM AUTHOR]

This article proposes an optimization‐based approach to selecting the sampling periods for classes of linear time‐invariant (LTI) regulators in a cascaded multi‐rate control structure, to account for practical implementation on numeric systems. Starting from the Shannon‐Nyquist sampling theorem, which proposes the minimum required sampling frequency for completely recovering the original analog signal from its discrete samples, the scope of the sampling process, viewed from a control perspective, is to ensure asymptotic stability of the closed‐loop system, with the smallest possible degradation of the initially‐proposed performance indices as possible according to a set of well‐picked criteria. As such, a configurable optimization‐based approach is proposed, solved with the mixed‐integer artificial bee colony (MI‐ABC) algorithm, for selecting the sampling periods by specifying the emphasis between closed‐loop fidelity and ease of implementation, with an intuitive visualization method. The proposed solution is illustrated on two case studies, with emphasis on the construction of the proposed functionals and their practical implications. [ABSTRACT FROM AUTHOR]

The application of cyber‐physical systems (CPSs) in many areas is threatened by its embedded structure. This paper considers the design of an adaptive controller for linear CPSs against deception attacks. Specifically, a corrective signal is designed to suppress or offset the impact of sensor and actuator attacks, especially when the controller and the correction signal are also attacked. First, an adaptive controller is developed for time‐invariant deception attacks and further extended to time‐varying deception attacks. In each case, state‐independent sensor attacks and input‐independent actuator attacks, as well as state‐dependent sensor attacks and input‐dependent actuator attacks, are discussed. For the considered closed‐loop system with time‐invariant state‐dependent sensor attacks and input‐dependent actuator attacks, the controller the authors developed ensures the asymptotic stability of the systems. For the other three cases of the corresponding system, the controllers are also designed, which ensures uniform ultimate boundedness. Finally, several numerical examples are given to explain the availability of our control scheme. [ABSTRACT FROM AUTHOR]

This paper concerns the improvement on Proportional‐Integration‐Derivative (PID) control for standard second‐order plus time‐delay systems (SOPTD). To achieve higher tracking precision and stronger disturbance rejection, a PID type‐ii and type‐iii control‐loops design method based on the combination of the linear quadratic regulator (LQR) and dominant pole configuration technology is proposed in this paper. The PID type‐ii control loop is capable of achieving perfect tracking of step and ramp reference signals with zero steady‐state position and velocity error. The PID type‐iii control loop is capable of achieving perfect tracking of step, ramp and parabolic reference signals with zero steady‐state position, velocity and acceleration error. The effectiveness of the proposed PID type‐ii and type‐iii controller parameters tuning rules has been demonstrated via simulation of over‐damped, critical‐damped and under‐damped systems. To be specific, compared with the PID type‐i control loop, rise time, settling time and disturbance rejection property of the system have been significantly improved while realizing faster reference signal tracking. Finally, the effects of non‐dominant pole on the stability and robustness of PID type‐ii and PID type‐iii closed loop systems have also been discussed. [ABSTRACT FROM AUTHOR]

The main focus of this research is on improving the performance of dynamic systems with actuator non‐linearities and time‐varying disturbances. To this end, using the concept of finite‐time stability, a novel observer is presented to estimate the disturbances in systems with input non‐linearities. Then, introducing an innovative sliding manifold, a robust observer‐based technique is derived to guarantee the finite‐time stability of the sliding surface. Hence, the closed‐loop system would be stable in the presence of hard non‐linearities and time‐varying disturbances. The performance of the proposed approach was assessed in using a simulation study of two numerical examples. The obtained results and comparison with a conventional method confirmed the benefits of the suggested approach. [ABSTRACT FROM AUTHOR]

A barrier Lyapunov functions‐based command filtered output feedback control scheme is presented for the electro‐hydraulic ammunition ramming system (EHARS) with position and velocity constraints in this paper. Due to the limitation of compact installation space in ramming mechanism, there remain some immeasurable signals such as the velocity of projectile and pressures in hydro‐cylinder; thus, a state observer is designed to estimate the unmeasured states of EHARS. The barrier Lyapunov functions theory is adopted to guarantee position and velocity constraints of projectile are not violated. In order to suppress the complexity of differential explosion in backstepping iteration, command filtered technology and corresponding compensating technique of filtering errors are applied. By the stability theory of Lyapunov, the stability of the closed‐loop system and the boundedness of the whole state in EHARS are theoretically proved. Simulation results show prescribed position‐tracking accuracy and desired velocity of projectile under different firing angles, which indicates the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Nowadays, interconnected cyber‐physical systems (CPSs) are widely used with increasing deployments of Industrial Internet of Things (IIoT) applications. Other than operating properly under system uncertainties, CPSs should be secured under unwanted adversaries. To mark such challenges, this paper proposes the solution of secure decentralized robust control for uncertain CPSs under replayed time‐delay and false‐data injection attacks altogether. Potentially, considered attacks can force the whole system to instability and crash. Three challenges are addressed, and solutions are presented: (1) model non‐linearity and uncertainties, (2) existing simultaneous time‐delay and potential false‐data injection attacks with skew probability density functions, and (3) requirement to use real‐time attack detection. Thus, a novel, robust control method to deal with thwart attacks on a closed‐loop control system is proposed to provide the system's trustworthiness. Additionally, novel attack detection methodologies are presented to detect these advanced attacks rapidly based on statistical methods such as Spearman's correlation coefficient, Neyman–Pearson (NP) error classification, and trend analysis. Ultimately, the proposed novel attack detection and robust control protocol are verified and evaluated in real‐time. [ABSTRACT FROM AUTHOR]

In this paper, the design problem of Gain‐Scheduled Output‐Feedback (GSOF) controllers using inexact scheduling parameters for morphing aircraft during the wing transition process is addressed. Both the stability of the closed‐loop system and the L2 gain performance can be guaranteed under the controller based on measured (not actual) scheduling parameters. Firstly, the linear parameter‐varying (LPV) model of morphing aircraft is established by Jacobian linearization and the additive uncertainty is introduced into the scheduling parameters. By employing non‐linear transformations, the problem is formulated as the solution to a set of parameter‐dependent linear matrix inequalities (LMI) with a single‐line search parameter. Finally, the robustness of the flight control system to the wing transition process is verified under the condition of both the uncertainty of aerodynamic parameters and of scheduling parameters. [ABSTRACT FROM AUTHOR]

The event‐triggered output feedback fault‐tolerant control problem is studied in this paper for interval type‐2 Takagi–Sugeno (IT2 T‐S) fuzzy large‐scale systems with time delays. First, a fuzzy state observer is designed to address the immeasurable states problem. Then, by introducing a discrete event‐triggered mechanism, an observer‐based event‐triggered fuzzy decentralized controller with dynamic parameters is synthesized in the presence of actuator faults based on the nonparallel distribution compensation (PDC) design principle. The sufficient conditions of asymptotic stability for the closed‐loop systems are derived by constructing an appropriate dynamic parameter based Lyapunov–Krasovskii functional candidate. Finally, a simulation example is provided to verify the feasibility of the developed fuzzy control method. [ABSTRACT FROM AUTHOR]

In this paper, asymptotic stabilization problem for a class of nonlinear systems with unknown time‐varying delays is addressed. With the introduced static gain functions and new Lyapunov–Krasovskii functionals, a novel output feedback control strategy is developed. A memoryless output feedback controller which does not need precise knowledge of time delays is designed. The asymptotic stabilization and the boundedness of the closed‐loop system are proved via Lyapunov analysis. Finally, numerical simulation validates the effectiveness of this method for the nonlinear time‐delay system. [ABSTRACT FROM AUTHOR]

In this paper, two novel algorithms to find the Nash equilibrium solution of the non‐zero‐sum games for continuous‐time input‐affine nonlinear systems are presented. Based on integral reinforcement learning method, the integral‐exploration‐coupled Hamilton‐Jacobi (HJ) equations are derived, which does not contain any information of the system dynamics. Then, based on neural networks approximation, two different adaptive tuning law of weights are given to estimate the approximate solution of the coupled HJ equations. Both two algorithms can estimate the value function and the policy without knowing or identifying the system dynamics. The closed‐loop system stability and the convergence of weights are guaranteed based on Lyapunov analysis. Finally, the simulation results of a two‐player non‐zero‐sum game demonstrate the effectiveness of our algorithms. [ABSTRACT FROM AUTHOR]

This paper focuses on the problem of adaptive integral sliding mode control (ISMC) with dissipativity for a type of complex non‐linear system represented by Takagi‐Sugeno (T‐S) fuzzy descriptor models. First, T‐S fuzzy descriptor systems with different derivative matrices are transformed into augmented systems that have the same properties as the original systems, and an integral sliding mode surface function is designed considering the descriptor matrices. Then, based on the dissipativity theory and the non‐parallel distributed compensation (non‐PDC) method, ISMC strategies and dissipativity‐based ISMC strategies are proposed, and the system uncertainties and external disturbances with unknown upper bounds are addressed with an adaptive controller. According to the Lyapunov theory and the dissipativity theory, a fuzzy Lyapunov function is designed, and the obtained criteria are presented in the form of strict linear matrix inequalities (LMIs); this approach guarantees that the closed‐loop system is asymptotically stable and strictly (Q,R,S)−α$(\mathcal{Q},\mathcal{R},\mathcal{S}) - {{\alpha}}$ dissipative. Moreover, the controller gain matrices and Lyapunov matrices are decoupled by introducing the corresponding auxiliary variables and employing Finsler's lemma. Finally, two examples are provided to illustrate the effectiveness and merit of the proposed method. [ABSTRACT FROM AUTHOR]

Distributed model predictive control (DMPC) approaches have achieved remarkable results in complex multiple subsystems network applications, such as unmanned aerial vehicle and sensor control networks. However, most of the existing DMPC algorithms require that the communication network of subsystems is time‐invariant or undirected with local constraints, by ignoring the cooperation of multiple subsystems with global constraint in the non‐ideal communication network, which greatly limits the applicability of the algorithms. To this end, the authors develop a fully DMPC algorithm of linear system with global constraint over time‐varying unbalanced directed communication. Considering the uncertainty of communication network, this algorithm can handle the non‐ideal communication network (e.g. communication noise, communication delay). Specifically, the row‐stochastic weight matrix is adopted to improve the independent controllability of subsystems. Under reasonable assumptions, it is proved that the algorithm can converge to the optimal solution while guaranteeing the recursive feasibility and exponential stability of closed‐loop system. Finally, the simulation experiments are shown to substantiate the convergence and robustness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper investigates the stochastic stability and stabilization of positive Markov jump linear impulsive systems (PMJLIS) with time delay. First, by choosing appropriate co‐positive Lyapunov–Krasovskii functional and using the impulsive average dwell‐time method, a stochastic stability criterion is provided for PMJLIS with time delay. Based on this criterion, for PMJLIS with time delay, the stabilization conditions are given using state feedback and impulse feedback, respectively. According to this criteria, the stochastic stability of the systems can be judged and the controllers can be designed only from some relations of the coefficient matrices, Markov jump parameters and delay. To illustrate the main results, a simulation example is provided at the end with a state‐feedback controller and an impulsive controller is designed, respectively, which makes the corresponding closed‐loop systems be positive, globally asymptotically stable in probability and globally asymptotically stable in mean. [ABSTRACT FROM AUTHOR]

This paper studies the distributed pulse‐width‐modulation (PWM) control problem for double‐integrator multi‐agent systems with switching topologies. Usually, a PWM control signal updates only on discrete‐time sample instants and only takes three constant values. This means that the methods based on linear and continuous designs are not directly applicable. The major contribution of this paper is that a new class of distributed PWM controllers, which feature nested saturated loops, is proposed. With the new design, the outputs of the controlled agents asymptotically converge to each other, as long as a mild connectivity condition is satisfied. The validity of the proposed PWM controller is proved based on a new invariant‐set‐like method. This work first shows that the state of each PWM‐controlled agent stays within an appropriately chosen closed set if the interactions are bounded. Then, under a mild connectivity condition, the state boundedness and convergence of the closed‐loop multi‐agent system by analyzing the boundedness of the interactions are proved. A numerical example is employed to verify the effectiveness of the proposed design. [ABSTRACT FROM AUTHOR]

This paper considers the output‐feedback controller for a class of stochastic cascade nonlinear systems with stochastic integral input‐to‐state stable inverse dynamics, unknown control coefficients, and matching disturbances. By augmenting the existing disturbance as an extended state, a novel extended state observer (ESO) is constructed based on the Riccati differential equation. Based on the techniques of Nussbaum function and backstepping, an adaptive output feedback controller is proposed to guarantee that all system states of the resulting closed‐loop system are globally asymptotically stable in probability. Meanwhile, the other signals are almost surely bounded. Additionally, the validity of the proposed control method is verified by simulation examples. [ABSTRACT FROM AUTHOR]

This paper proposes an anti‐wind up double hyperbolic sliding mode controller (AWDH‐SMC) in the presence of torque constraints for a three‐legged robot. The legged robot's dynamics are nonlinear, hybrid and complex. Based on the challenges mentioned, this study focuses on designing a sliding mode controller (SMC) for a fully actuated three‐legged robot to achieve fast tracking and convergence. On the other hand, the torques generated by the actuators are limited. As a result, not only must the controller be fast so that the robot's balance is not disturbed, but it must also withstand applied torque constraints. Therefore, the double hyperbolic sliding mode controller is designed at first for fast tracking and convergence. Next, an anti‐wind up compensator is used to apply torque constraints. Finally, using the theory of multiple Lyapunov functions, the stability of the closed‐loop control system for the hybrid model of legged‐robot is analyzed. Simulation results validate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

In this article, an adaptive fuzzy finite‐time fault‐tolerant control (FTC) scheme for uncertain non‐linear systems under sensor faults is proposed. Compared with the existing methods, the considered system contains unknown time‐varying fault parameters, uncertain non‐linear functions, and can guarantee the performance of the system in finite time. The coupling between fault parameters and actual states is solved by the fault parameters separation method. The fuzzy logic system (FLS) is used to approximate the unknown functions, and combining the backstepping technology an adaptive fault‐tolerant controller is designed. The finite‐time stability of the closed‐loop system is proved by the Lyapunov theory. At last, the numerical simulation and the real physical system simulation verified the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In recent years, bioreactor control is very important due to the challenges associated with the highly non‐linear behaviours. The dynamical structure of the system has been extended compared to previous researches and correspondingly the controller configuration is developed in this approach. This approach deliberates an event‐triggered adaptive fault‐hiding prototype for the non‐linear affine bioreactor system. Since this controller has the ability to hide the faults and external disturbances effects, the separated fault detection, isolation, and identification unit are not required in this approach. Also, the measurement information is triggered by the incidence of a certain event to amend the network resources. The focal advantages of the planned methodology are: (1) Robustness of the planned approach against external disturbances, (2) the presented virtual actuator conceals mechanism faults, (3) the convergence of tracking errors in the presence of both the faults and the external disturbances is guaranteed to neighbourhood of zero, and (4) significantly reducing data exchange based on event‐triggered strategy with a state‐independent threshold. The stability of closed‐loop system is guaranteed based on Lyapunov approach. The simulation results show that the proposed fault‐tolerant approach on the bioreactor systems is effective. [ABSTRACT FROM AUTHOR]

This paper aims at the tracking control problem of the non‐strict‐feedback non‐linear systems with non‐constant unknown delays and full state constraints. A constrained exponential Lyapunov–Krasovskii function‐based fuzzy adaptive dynamic surface control (CELK‐FADSC) method is proposed. In order to achieve the goal of full state constraints, the tan‐type Barrier Lyapunov function (BLF) is used. Furthermore, to reduce the influence of the non‐constant unknown delays on the system, an exponential Lyapunov–Krasovskii function is constructed. At the same time, sliding mode differentiator is adopted to the dynamic surface control (DSC) method, by which the 'complexity explosion' problem in backstepping is solved. In addition, the proposed adaptive tracking controller can ensure that the states in the closed‐loop system do not violate their constraint, and the semi‐global uniformly ultimately bounded (SGUUB) can be achieved. Finally, simulation outcomes can prove the validity of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, the cooperative distributed model predictive control (DMPC) problem of a class of complex systems consisting of several subsystems is studied. The states of these subsystems are coupled with each other, and thus bring challenges for the model predictive control algorithm. Moreover, though the subsystems can communicate with each other, they only can access to the output information of their neighboring subsystems. In this case, Luenberger observers are used to estimate the unknown states and a distributed prediction strategy is established for the studied system. Then, the optimal control of the closed‐loop system is realized by designing distributed model predictive controller on the basis of the estimated states. The terminal constraints are introduced in the proposed DMPC algorithm to ensure the iterative feasibility and also the stability of the closed‐loop. Finally, the effectiveness of the proposed method is verified by a numerical simulation. [ABSTRACT FROM AUTHOR]

A geometric control is proposed for the trajectory‐tracking of a quadrotor unmanned aerial vehicle with suspended load. The plant to be controlled is modelled by using Euler–Lagrangian equations, and it is linearised around zero swing angles of the load. The swing angles of the load are supposed to be unmeasurable, and they are estimated by the state observer. The controller is design in the inner–outer loop framework, where the outer loop trajectory‐tracking is basically implemented by internal model principle, and the inner loop attitude control is designed on SO(3)$SO(3)$ to avoid singularities. It is proved that, with the proposed geometric control, the tracking error of the inner loop converges in finite time, and the outer loop trajectory tracking error is asymptotically stable. Theoretical results are substantiated by a numerical example, where the closed‐loop system is capable of tracking a circular curve. [ABSTRACT FROM AUTHOR]

This paper investigates a fixed‐time terminal sliding mode (TSM) control scheme of second‐order non‐linear uncertain systems. A globally fast fixed‐time stable system is proposed, and the convergence time is established with the Lyapunov method. Then, a novel non‐singular TSM utilising the proposed fixed‐time stable system and an auxiliary polynomial function is constructed. Meanwhile, a fixed‐time disturbance observer technique is employed to estimate the matched lumped perturbation. Globally fast fixed‐time convergence of the closed‐loop system is guaranteed with the phase plane analysis and Lyapunov tools, and the upper bound of the settling time independent of the initial conditions can be predefined by the controller parameters. Finally, the simulation results of a single inverted pendulum system are included to confirm the validity of the proposed methodology while comparing with some popular TSM control strategies. [ABSTRACT FROM AUTHOR]