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This paper addresses the stochastic communication protocol (SCP) based controller design problem for discrete delayed system with stochastic uncertainty and Markovian packet dropouts. This issue is frequently occurred in networked control system where the packet dropouts bring obstacle for controller design. Especially, the controller terms are not allowed to be transformed directly into actuator side under the SCP. Thus, the traditional approaches are not effective to solve this design issue. In this paper, a novel sliding mode control (SMC) mechanism is given to handle the influences caused by packet dropouts, time-varying delay and SCP. A protocol-based controller is designed to guarantee that the closed-loop system is mean-square asymptotically stable with satisfactory H ∞ performance. Moreover, an optimization algorithm is further provided to compute the protocol-based gain matrix. Finally, a simulation example is proposed to verify the effectiveness of the presented protocol-based SMC design procedure. [ABSTRACT FROM AUTHOR]

This paper studies the dynamic output feedback (OF) control problem for unmanned aerial vehicles (UAVs) with limited network bandwidth by a genetic-algorithm-assisted design approach. In order to make full use of the limited network bandwidth, only partial measurement information is transmitted to the controller via the sensor-to-controller network. Round-Robin protocol is introduced to administrate the transmission rule. Sufficient conditions are presented to make sure that the closed-loop UAV system is exponentially stable with the required L 2 -gain performance. However, due to the nonlinear coupling terms of the dynamic OF controller parameters and some redundant variables in the system modeling, the established conditions are non-convex and difficult to be solved. Fortunately, genetic algorithms (GA) show good performance in solving optimization problem with nonlinear and non-convex constraints. Therefore, this paper skillfully combines GA with linear matrix inequality techniques to solve the established conditions. Finally, all the dynamic OF controller parameters and the minimal L 2 -gain can be obtained simultaneously. At the end of this paper, an UAV networked control example and a numerical example are performed to verify the effectiveness and superiorities of our method. [ABSTRACT FROM AUTHOR]

• For the fast-varying delay, an improved analytical method based on Lyapunov-Krasovskii (LK) functionals is given by introducing and proving a new lemma, which is not only independent of the upper bound of time-varying delay, but also independent of the derivative of the time-varying delay. Hence, the developed analytical method greatly expands the application range of the LK functional. • For unknown nonconstant control coefficients, an output feedback control strategy based on the compensated system is proposed. As an intermediate link, the adaptive fuzzy system is introduced into the controller indirectly by the compensation system, so as to avoid the algebraic-loop problem. Hence, the cooperative design of the compensation system, the state observer and the controller is one of the innovations in this paper. • Considering the problems of state immeasurability and time-varying delay comprehensively, an adaptive fuzzy output-feedback control law is proposed based on an improved average dwell time, which relaxes the constraints between the LK functional of each subsystem in switched large-scale interconnected nonlinear systems. In this paper, an adaptive fuzzy decentralized output-feedback control is developed for the uncertain switched large-scale interconnected nonlinear system, which contains fast time-varying delays and unknown nonconstant control coefficients. By introducing and proving a new lemma, an improved analysis method is given based on the Lyapunov-Krasovskii (LK) functional, and it gets rid of the dependence of LK functional design on the bound of the derivative of the delay. Immeasurable states are estimated by co-designing the decentralized state observer and the innovative compensation system, which eliminates a widely adopted but strict assumption that the unknown control coefficient must be constant. By comprehensively designing the state observer, the compensation system and LK functionals, a novel adaptive fuzzy decentralized output-feedback control law is proposed, and stability of the closed-loop system is guaranteed theoretically based on an improved average dwell time. Finally, the effectiveness is further verified by complete simulation experiments. [ABSTRACT FROM AUTHOR]

The fixed-time tracking control issue is investigated for a class of high-order nonlinear delayed systems subject to mismatched disturbances in this paper. Wherein, the fuzzy logic system is applied in dealing with the nonlinear functions and the power integrator technique is appropriately introduced to address the high-order terms in the considered system. Different from the conventional methods of using the Lyapunov-Krasovskii functional approach to cope with the delayed terms in the previous work, the adaptive backstepping method is utilized in this paper. The main purpose of the addressed control problem is to design a suitable adaptive fuzzy fixed-time controller such that the closed-loop system is stable and guaranteed to be bounded in a fixed-time interval. Subsequently, the specific control law is deduced through the inductive method, and the upper bound on the settling time for the fixed-time control is given. Finally, the simulation examples are given to illustrate the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper investigates the adaptive fixed-time tracking control problem for a class of stochastic nonlinear systems with constrained states and input saturation. By utilizing a barrier Lyapunov function (BLF), the issue caused by constrained states is settled. Simultaneously, a smooth function is constructed to approximate input saturation and the unknown nonlinear function is approximated by neural networks (NNs). In view of the fixed-time tracking control problem of stochastic nonlinear systems, a fixed-time stability lemma for stochastic nonlinear systems has been established and proved. Under the designed controller, the closed-loop system is semi-globally fixed-time stable in probability (SGFSP), and all the states are constrained within a compact set. Moreover, the controlled system in this paper achieves equilibrium within a fixed-time internal. Lastly, the presented method is verified by a simulation example. [ABSTRACT FROM AUTHOR]

In this paper, the finite-time control and bumpless transfer control are investigated for switched systems under asynchronously switching. First, a class of dynamic output feedback controllers are designed to stabilize the switched system with measurable system outputs. Considering the improvement of transient performance, the bumpless transfer control and finite-time control are further studied in the controller design. To avoid the control bumps, a practical filter is introduced to make the control signal smoother and continuous. Furthermore, to derive a finite-time bounded system state over short-time intervals, the finite-time analysis is considered in managing the switching process with the average dwell time. New criteria are proposed to analyze the finite-time stability and finite-time boundedness for the closed-loop system and solvable conditions are newly proposed to optimize the controller gain. Finally, the superiorities of the proposed method are validated through an application to a boost converter. [ABSTRACT FROM AUTHOR]

This paper contributes to the problem of tracking control for nonlinearly vibrating structure supporting a vibrational mass-carrying string with unknown string tension. The control scheme is constructed based on optimally designed reaching law considering actuator force limit, parametric uncertainties and Lyapunov stability conditions. The reaching law is designed through real-time detection of stability margins and analyzing actuator capabilities such that system dynamics are either driven into reaching or attraction phase in finite time. The control algorithm boasts robustness against parametric uncertainty by narrowing stability bounds and features an online string tension estimation engine based on data analysis obtained from acceleration and proximity sensors measurements. In order to provide smooth tracking, string vibration suppression is achieved by incorporating corresponding dynamical terms in construction of control algorithm. The closed-loop system is simulated alongside conventional discrete sliding mode technique, the results of which are compared and analyzed to pinpoint viable advantages. [ABSTRACT FROM AUTHOR]

This paper investigates the design of fault-tolerant adaptive event-triggered integral sliding mode control (FTAETISMC) for a class of uncertain systems in the presence of partial actuator failures. The proposed control scheme guarantees the closed-loop system to operate properly in case of partial actuator failures and ensures the reachability of the sliding mode surface. In order to reduce the consumption of system resources, an adaptive event-triggered (ET) mechanism is introduced, where the threshold is based on a function of a non-negative adaptive parameter. By choosing the parameter of the integral sliding mode manifold, the asymptotic stability of the system can be achieved. To ensure that the system does not suffer from Zeno phenomenon, there exists a positive lower bound of the inter-event time. Finally, simulation results of a numerical example are presented to prove the benefits of the proposed method. • A networked control systems with matched and unmatched uncertainties under actuator failures is discussed. • A robust controller with integral sliding mode can eliminate uncertainties. • An adaptive event-triggered mechanism is proposed. • A minimum positive lower bound on the inter-event time to avoid Zeno phenomenon is obtained. [ABSTRACT FROM AUTHOR]

This paper investigates the consensus problem for nonlinear multiagent systems (MASs) with unknown time-varying measurement sensitivity and infinite communication delays. Unlike existing works, the output measurement sensitivity is described as time-varying, and an infinite communication delay is considered between the agents. Under this condition, a novel output feedback control algorithm is developed. First, based on the hierarchical technique and Lyapunov-based time-domain method, the high-gain compensator and observer are constructed to tolerate the effect of infinite communication delays and accurately estimate the state of the leader. Subsequently, a new distributed k-filter and output feedback controller are proposed, which not only further relax the traditional Lipschitz conditional conservatism but also greatly simplify the design process. It is proved that the closed-loop system is globally stable and all agents can achieve consensus. Finally, the effectiveness of the proposed method is verified through the simulation of the single-link manipulators. [ABSTRACT FROM AUTHOR]

The path planning and tracking control problem of autonomous vehicle with model matched uncertainty and external disturbance is studied in this paper. A safe lane change zone is designed by considering lane change time, distance, and driving speed. Meanwhile, the candidate paths are generated using cubic quasi-uniform B-spline curve, and the optimal path is selected based on feasibility, comfort, and efficiency criteria. The proposed planning method ensures an efficient and comfortable lane change path without collision with surrounding vehicles. Model uncertainty and external disturbance may affect lane change tracking control of autonomous vehicle. Hence, a fault-tolerant path tracking controller is implemented by using deep neural networks and adjustable zonotope-tube model predictive control. A deep neural network-based controller is proposed to compensate for model matched uncertainty, thereby enhancing the fault tolerance of the control system. Then, an adjustable zonotope-tube model predictive controller is designed to enclose the actual trajectory within a zonotope-tube with the nominal state as the center and the disturbance set as the radius by using the feedback control to achieve the asymptotic stabilization of the closed-loop system. The effectiveness of this path planning and tracking control method is finally verified by numerical simulation. • A lane change path planning method suitable for structured roads is proposed, which is based on the utilization of a safe lane change zone and cubic quasi-uniform B-spline curves. The proposed method ensures an efficient and comfortable lane change path. • A fault-tolerant path tracking controller is presented for autonomous vehicle, which incorporates a deep neural network and adjustable zonotope-tube model predictive control. The controller effectively handles model uncertainty and external disturbances. • The computation of robust positive invariant set is performed using the adjustable zonotope-tube method, which enhances scalability and reduces computational cost. [ABSTRACT FROM AUTHOR]

We consider the inherent attack tolerance properties of resilient model predictive control (R-MPC) for cyber–physical systems (CPSs) modeled by discrete linear time-invariant (LTI) systems subjected to limited disruptions. In this paper, the relationship between the maximum allowable duration of Denial-of-Service (DoS) attacks, namely attacks that disrupt both sensor to controller (S–C) and controller to actuator (C–A) communication channels, and the upper bound of disturbances is deduced at length. Moreover, to achieve robust recursive feasibility and closed-loop stability of the system, we discuss that MPC with state, control and terminal constraints has a certain degree of inherent attack tolerance concerning the DoS attack duration and parameters like system matrices and the nominal terminal set. Finally, numerical simulation is given to substantiate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper aims to provide a data-driven approach for modeling the longitudinal dynamics of a typical ground vehicle with a gasoline engine and automatic transmission. In the identification process, a Linear Parameter Varying (LPV) model is considered, whose inputs are throttle level and road grade and whose parameters vary as a function of throttle level and gear number to capture the nonlinear dynamics. Three parametric structures based on time-series modeling (ARX, ARMAX, BJ) are investigated, whose performances are discussed comparatively. In addition to selecting the best structure, an optimization problem is proposed to acquire the optimal model order of these structures. It is shown, using semi-experimental tests on the CarSim® software package, that the dynamics of different vehicles can best be represented by different model orders. To evaluate the versatility and utility of the proposed LPV model, a PI controller is tuned using the model, and the closed-loop performance of the system is compared against the model. It is shown that the LPV model is very accurate in closed-loop settings. [ABSTRACT FROM AUTHOR]

This paper studies states estimation and resilient control schemes based on model predictive control (MPC) algorithm for a class of Takagi–Sugeno (T–S) fuzzy stochastic distribution control (SDC) system subjected to sparse sensor attacks. Firstly, a T–S fuzzy model is used to approximate the dynamics of a non-Gaussian SDC system, where the outputs of the system is the output probability density functions (PDFs). Secondly, in order to estimate the states and attacks in the system, a fuzzy Luenberger observer is designed. In addition, based on the estimated states and attacks, the designed MPC resilient control method achieves a satisfied tracking performance. Finally, the feasibility of the estimation algorithm and resilient controller are verified by simulation. • A T–S fuzzy model is established for SDC systems to approximate the output PDFs. • A fuzzy Luenberger observer is designed to estimate the augmented states and attacks. • A resilient controller is proposed to ensure the stability of the closed-loop system. • The feasibility of the proposed algorithm is verified by simulation. [ABSTRACT FROM AUTHOR]

A fixed-time controller based on improved fixed-time predictor line-of-sight (FxTPLOS) guidance and a nonsymmetrical prescribed performance constrained controller is designed for the path-following of underactuated marine surface vehicles (MSVs) in the presence of unknown external disturbances and uncertainties. First, a fixed-time error prediction model is established, and an internal model-controlled observer is designed to observe the sideslip angle, which can extend the estimated range of the sideslip angle to any range. Second, a nonlogarithmic performance function is introduced that can converge the error to a prescribed range, and a fixed-time controller is designed by error transformation. A new input saturation function is added to solve the problem of input saturation, and a new filter is added to avoid differentiating the virtual control law. Third, a novel fixed-time lumped disturbance observer is proposed for estimating the model uncertainty and external disturbances. It is possible to achieve accurate disturbance compensation. By using Lyapunov theory to analyze the stability of the closed-loop control system, it is proven that the system can be uniformly globally fixed-time stable (UGFxTS). Finally, simulation experiments prove that the control strategy proposed in this paper is effective. [ABSTRACT FROM AUTHOR]

We present a dynamic output feedback fuzzy model predictive control (FMPC) approach for the Takagi–Sugeno model with bounded disturbance in this paper. The proposed approach relies on the formulation, at each sampling instant, of a lexicographic optimization problem that takes into account multiple objectives including improving the control performance, enlarging the region of attraction (ROA) and tightening the estimation error set (EES). Since the controller parameters and Lyapunov matrices are kept as degrees of freedom for the lower-ordered optimization problems, larger ROA and less conservative EES are obtained. As a result, the control performance can be greatly improved with respect to previous works. Furthermore, we prove the recursive feasibility of the approach and guarantee the stability of the closed-loop system. The result is verified through a numerical example. [ABSTRACT FROM AUTHOR]

This paper addresses a fault-tolerant formation tracking problem for multiple mobile robots, where the dynamics of each robot is nonholonomic with time-varying input delays and actuator faults. The control problem is challenging since the actuator faults (e.g., loss of effectiveness and biased faults) are unknown in the time-delay multi-agent systems. To this end, an adaptive compensator is proposed for the uncertain time-delay systems induced by the loss of effectiveness faults. With the aid of neural networks and auxiliary variables, a novel adaptive fault-tolerant formation tracking controller for each robot is developed without any restrictions on the rate of their unknown variables induced by the biased faults. The uniformly ultimately boundness for the closed-loop system is derived according to the Lyapunov–Krasovskii functional. Numerical simulations verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, a class of interconnected systems is considered, where the nominal isolated subsystems are fully nonlinear and non-minimum phase. A decentralized Extended Kalman Filter-Extended High Gain Observer (EKF-EHGO) is designed to observe the system states. Then, a systematic backstepping design procedure is employed to develop a novel decentralized robust adaptive output feedback control, in which the adaptive law is designed to counter the effects of the interconnections and uncertainties. The proposed decentralized dynamic output feedback control scheme can guarantee that all the signals in the closed-loop system are uniformly ultimately bounded (UUB). Both interconnections and uncertainties are allowed to be unmatched and bounded by an unknown high-order polynomial, which is a more general form when compared with existing work. Two MATLAB simulation examples are used to demonstrate the effectiveness of the proposed method including a system comprising translational oscillator with rotating actuator (TORA) sub-systems. [ABSTRACT FROM AUTHOR]

In this paper, a velocity estimation-based adaptive dynamic surface asymptotic tracking control strategy for electro-hydraulic actuator (EHA) systems subjected to uncertainties and unmeasurable velocity is proposed. Firstly, an accurate velocity signal is estimated by constructing a new state observer, reducing the influence of measurement noise, system cost, and installation complexity. Moreover, the observer's robust gain is updated by an adaptive law, reducing the conservativeness of its selection. Then, a continuous friction model based on the desired velocity signal is used for feedforward compensation to alleviate the negative effect of estimation noise. Moreover, the adaptive dynamic surface control (ADSC) technique is incorporated to avoid "complexity explosion" and eliminate filtering errors via adaptive terms. Finally, the asymptotical stability of the closed-loop system is theoretically proved via Lyapunov analysis, while the efficacy of the proposed control strategy is experimentally validated and numerically verified. [ABSTRACT FROM AUTHOR]

This paper investigates the finite-time (FT) adaptive output feedback control for a class of nonlinear systems with asymmetric state-function constraints and unknown external disturbances. Incorporating the asymmetric barrier Lyapunov function (BLF) into the backstepping technique, a new control approach is proposed to ensure that all states do not cross the constraint boundary. With the help of the command filter, the explosion of complexity induced by repeated differentiations of virtual controllers is eliminated, and the corresponding compensation system is used to offset the filter error. Meanwhile, the fuzzy logic system (FLS) and fuzzy state observer are employed to approximate unknown nonlinear functions and estimate unmeasurable states respectively. For effectively conserve communication resources, a novel adaptive event-triggered controller is proposed such that all signals of the closed-loop system are bounded, the tracking error converges to a small neighborhood containing the origin in finite time. Finally, the feasibility of the fabricated control scheme is verified with two examples. [ABSTRACT FROM AUTHOR]

This paper explores the finite-time boundedness and controller problem of switching nonlinear delay systems. The time delay is considered as time-varying delay rather than constant delay. First of all, an appropriate Lyapunov–Krasovskii functional (LKF) which contains three integral terms is selected. The upper and lower bounds of these integral terms are given by segmenting the time delay interval. Meanwhile, the auxiliary matrix method is used to separate the Lyapunov matrix from the system matrix. Moreover, a new state-dependent switching law is designed to switch between subsystems according to the change of the magnitude of the LKF. Based on the above methods, the first step is to research the finite-time bounded analysis of delayed system without control input. Then, a sufficient condition is obtained to ensure the finite-time boundedness of switched systems with control input. Further, by designing an observer-based H ∞ controller, the closed-loop system with time-varying delay is bounded and has H ∞ performance index ν by using the Finsler's Lemma and Singular Value Decomposition (SVD). Simultaneously, the controller and observer gains are designed. Finally, two simulations are used to verify the effectiveness and feasibility of the proposed methods. • Investigating the finite-time boundedness and H ∞ control for switching nonlinear delay systems. • The time delay is considered as time-varying delay rather than constant delay. • Three integral terms are contained in the Lyapunov–Krasovskii functional. • The auxiliary matrix method is used to separate the Lyapunov matrix from the system matrix • A new state-dependent switching law is designed to switch between subsystems. [ABSTRACT FROM AUTHOR]

This paper is focused on the stochastic stability and controller design of descriptor Markovian jump systems with time-varying delays. For achieving this goal, systems are decomposed into differential-algebraic equations firstly. A modified mode-dependent Lyapunov-Krasovskii functional (LKF) and a memory state feedback controller are constructed on the basis of the state decomposition. Then, combining the auxiliary functions integral inequality and the extended reciprocally convex matrix inequality (ERCMI), an ameliorative stochastic stability criterion is obtained. Based on this novel stability condition, the designed controller is used to make sure the closed-loop systems are stochastically stable. Finally, the effectiveness of presented results is confirmed with some numerical examples. [ABSTRACT FROM AUTHOR]

• A novel event-triggering mechanism and three dynamic gains are introduced to compensate uncertainty and execution error. • It overcomes difficulties from unknown polynomial growth rate, unknown large measurement sensitivity and time-delay. • It proves that all the signals are bounded, the states converge to zero asymptotically, and the Zeno behavior is excluded. In this paper, the problem of adaptive event-triggered output-feedback stabilization is addressed for a class of switched nonlinear systems with time-delay and output measurement sensitivity. With the assistance of the dynamic high gain technology and a novel event-triggered control mechanism, we overcome the design complexities arising from unknown polynomial growth rate with respect to the output, unknown large measurement sensitivity, unknown time-varying control coefficient and time-delay. Then, an effective constructive method is provided to design switched observers and a common event-triggered controller. Through introducing two key matrix inequalities and constructing a common Lyapunov-Krasovskii functional, sufficient conditions are given to get rid of Zeno behavior, and ensure that all the signals are bounded and the closed-loop system states converge to zero under arbitrary switchings. Two simulation studies are conducted for verifying the effectiveness of proposed scheme. [ABSTRACT FROM AUTHOR]

This paper discusses the event-triggered composite anti-bump H ∞ control problem for the networked switched systems in the finite-time stability sense. An event-triggered scheme (ETS) is constructed to reduce resource usage while maintaining desired control performance. Then, a novel switching bumpless control method based on ETS is given to resist the impact of bump transition between different modes. Sufficient criteria for finite-time boundedness of the closed-loop systems with bumpless transfer characteristics and H ∞ performance are derived by resorting to a mode-dependent average dwell time (MADT), and a trigger-based bumpless transfer controller is designed. Finally, a simulation example is provided to demonstrate the efficacy and feasibility of the proposed control strategy. [ABSTRACT FROM AUTHOR]

• A composite error transformation for addressing the initial condition dependence issue. • Cross-backstepping control with prescribed performance for underactuated systems. • The stability of closed-loop systems is rigorously analyzed. • Two typical numerical examples are conducted. [Display omitted] Underactuated robotic systems with input coupling are widely applied in practice. However, designing controllers for such systems poses significant challenges due to the complexities arising from input coupling. To address this issue, this paper proposes a novel cross-backstepping control strategy based on a composite error transformation. The transformation compresses the system's initial error into a definable range to deal with the issue of initial value dependency of prescribed performance control, while maintaining the transient and steady state of the system. Based on such a technique, a cross-backstepping controller is proposed whose core idea lies in constructing a virtual term that crosses with coupled states to generate a unified form, which serves as a bridge between multiple coupled states and a single actual control input. Furthermore, a nonlinear disturbance observer is introduced to improve the robustness of the system. The stability of the closed-loop system is proved according to the Lyapunov theorem, and two numerical examples of underactuated robotic systems with coupled inputs are presented to demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper focuses on the security control of a discrete-time switched power system utilizing a probabilistic event-triggered protocol under a multi-strategy deception attack. To better characterize the system mode's switching behavior, a novel nonhomogeneous sojourn probability is introduced, which is modulated by a upper-level deterministic switching signal. Furthermore, a multi-strategy deception attack is established, wherein different deception attack strategies randomly target various nodes during signal transmission through the network carrier to the controller. To optimize network resource utilization, a probabilistic event-dependent triggering protocol based on a triggering threshold interval is presented, which effectively reduces unnecessary communication, leading to resource savings. Subsequently, sufficient conditions for the closed-loop system's input-to-state stability in probability is derived. Finally, the effectiveness of the proposed control strategy is demonstrated through simulation results, which verify its capability in enhancing system security and stability, while efficiently utilizing network resources. [ABSTRACT FROM AUTHOR]

The robust H ∞ dynamic output feedback (DOF) control for a class of nonlinear time-varying delay rectangular descriptor Markov jump systems (DMJSs) is discussed in this paper, there are no restrictions on the rows and columns of the differential matrix E. The rectangular DOF controller is designed to make the closed-loop system as square DMJSs. Firstly, by utilizing a mode-dependent and delay-dependent Lyapunov-Krasovskii (L-K) functional and implicit function theorem, sufficient conditions are given to guarantee that the augmented closed-loop systems are robust stochastically admissible with an H ∞ performance and have unique solution simultaneously. Then based on certain matrix decoupling techniques, a new strict linear matrix inequality (LMI) sufficient condition for the existence of a rectangular DOF controller is obtained, and the controller is given. Finally, numerical examples are presented to verify the validity of the results. [ABSTRACT FROM AUTHOR]

The adaptive tracking problem for a class of strict-feedback switched nonlinear systems with output constraints, quantization input, distributed time-varying delays and external disturbances is studied in this paper. Firstly, we introduce the hyperbolic tangent function to handle the quantized signal in the design of the controller. For the nonlinear term and distributed time-varying delay of the system, the integral term is introduced into the candidate functional to compensate it. Secondly, based on Dynamic Surface Control (DSC) technique and Barrier Lyapunov function (BLF) method, an adaptive controller is designed to guarantee the stability of the controlled closed-loop system, and the system tracking error can converge to the origin without violating the constraints. Finally, simulation results verify the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper studies the problem of event-triggered adaptive control for a class of strictly-feedback stochastic nonlinear systems. The output dead zone and time-varying full-state constraints are considered in the controller. Firstly, time-varying barrier Lyapunov functions (TVBLFs) are introduced to address problems of time-varying state constraints. Then, the Nussbaum-type function is used to compensate for the influence of the output dead zone. The problem of state constraint is well solved when the system's output signal is affected by the dead zone, which satisfies a wider application space. In addition, a new relative threshold of the event-triggered control (ETC) scheme is considered to save communication resources, and the Zeno behavior is excluded. This scheme makes the trigger interval more flexible and optimizes the performance of the controller. Moreover, the error compensation signals reduce the filtered errors and simplify the algorithm. Simultaneously, an adaptive tracking controller with the backstepping technique is designed so that all signals in the closed-loop system are bounded and the tracking error converges to a small residual set of the origin. Finally, two simulation examples are given to demonstrate the effectiveness of the control method. [ABSTRACT FROM AUTHOR]

This paper proposes a hierarchical event-triggered approach for distributed formation tracking of multiple autonomous surface vehicles (ASVs). The kinematic and dynamic loops are developed to generate the guidance law and the control efforts respectively. In the kinematic loop, a surrogate model is developed for each ASV, so that the kinematic states of the ASV can be predicted by its neighbors. Only when a predefined event-triggering condition is satisfied, will the ASV's true states be broadcast for updating the corresponding surrogate model, which circumvents the continuous states exchanges between ASVs. Additionally, a distributed leader motion observer is constructed to estimate the virtual leader's velocities to avoid acquiring global information. In the dynamic loop, a novel event-triggered extended state observer is developed, by which the velocity tracking errors and the model uncertainties are estimated online and transmitted to a dynamic-inversion based controller only when necessary. The communication loads in sensor-to-controller and controller-to-actuator channels are thus simultaneously reduced. The stability of the closed-loop system is rigorously proved by the Lyapunov theory and cascade system theory. The Zeno behavior is also well excluded in multiple channels. Simulation results show that the proposed scheme has satisfactory control performances and distinct features of low communication burdens and energy consumption. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of network-based sliding mode observer design and stabilization for nonlinear semi-Markovian jump systems. To design the observer, an event-triggering condition relies on network framework is proposed based on the system output measurement that transmitted through communication channel. Relying on the estimated state, an integral sliding surface is proposed and corresponding sliding mode controller is constructed to guarantee finite-time reachability of predefined sliding surface. In the analysis of sliding mode dynamics and error dynamics, it is considered that the transition rate information suffer from more generally uncertain cases, especially for the type that the mode jumping information from mode to others are totally unknown. Even so, sufficient conditions are developed to ensure stochastic stability of the overall closed-loop system. Finally, a numerical example is provided to verify the effectiveness of the established method. [ABSTRACT FROM AUTHOR]

This paper considers the robust H ∞ guaranteed cost control problem for singular continuous-time semi-Markov jump systems. In quadratic cost function, the weighting matrices are indefinite. First, sufficient conditions are given which ensure the related closed-loop systems to be stochastically admissible with γ -disturbance attenuation, and the value of the cost function is bounded between zero and the positive upper bound. Then, by a new linear matrix inequality(LMI) method and a matrix decoupling technique, the reducible dynamic output feedback guaranteed cost controllers with full order or reduced order are designed. Last, the effectiveness of the proposed methods is illustrated by two examples. [ABSTRACT FROM AUTHOR]

This paper studies the fault-tolerant control (FTC) problem of a class of strict-feedback nonlinear systems. First, we put forward a key theorem which shows that type-B Nussbaum functions can be extended to the cases containing multiple Nussbaum functions in the same Lyapunov inequality under certain conditions. Then, by using the techniques of Nussbaum functions and adaptive control, a new fault-tolerant control scheme is proposed. Compared with the previous work, this paper considers unknown time-varying control coefficients and unknown time-varying fault coefficients of actuators. It is proved that all the signals of the closed-loop system are globally bounded and the tracking error converges to zero asymptotically. Finally, simulations are provided to verify the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper addresses the observer-based dynamic event-triggered (DET) sliding mode control (SMC) problem for fuzzy singular semi-Markovian jump systems (FSS-MJSs) subject to generalized dissipative performance, in which a novel double-quantized structure is reasonably merged into a unified model. The main aim of this paper is to develop a mode-dependent adaptive sliding mode control (ASMC) law through the DET rule, which not only makes the closed-loop systems mean-square admissibility and generalized dissipative, but also the finite-time reachability around the predefined sliding mode surface (SMS) can be achieved. Firstly, in order to improve the data transmission efficiency and save network bandwidth resources, DET and doubled-quantized-based control protocol are introduced, in which the event-based threshold function is dynamically regulated and the data of input and output are both quantized; Secondly, due to the sensor information constraints, system state information is not always obtained in practice, hence, a suitable observer design can make up for this defect. Meantime, in terms of elegant linearization technique and implicit function theorem, the uniqueness of the solution for FSS-MJSs is also established; Additionally, by making use of the Lyapunov functional and linear matrix inequality (LMI) technique, both the desired SMC gains, observer gains and triggering parameter matrices are co-designed, more than that the derivative singular matrix is also integrated into the whole design process such that the derived conditions are much more easily to be checked; Finally, a numerical example and a practical application example are co-given to verify the effectiveness of our design mentality. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of two-dimensional (2D) system-based preview repetitive control (PRC) with equivalent-input-disturbance (EID) for uncertain continuous-time systems. First, to use the available values of the reference signal, we construct an equality constraint which includes the output of a basic repetitive controller, preview compensation and tracking error. Next, to compensate the unknown external disturbances, we incorporate an EID estimator into the PRC controller. Then, by employing the 2D system theory together with the linear matrix inequality (LMI) approach, we derive a sufficient condition to ensure the robust stability of the closed-loop system. By solving an LMI, the gains of the controller and state observer can be obtained. The results obtained in this paper generalize and include some results in the existings. literature. Finally, a numerical simulation demonstrates the effectiveness and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, the optimal model reference adaptive control (MRAC) problem is studied for the unknown discrete-time nonlinear systems with input constraint under the premise of considering robustness to uncertainty. Through an input constraint auxiliary system, a new adaptive-critic-based MRAC algorithm is proposed to transform the above problem into the optimal regulation problem of the auxiliary error system with lumped uncertainty. In order to realize the chattering-free sliding model control for the auxiliary error system, an action-critic variable is introduced into the adaptive identification learning. In this case, the closed-loop control system is robust to the disturbance and the neural network approximation error. The uniformly ultimate bounded property is proved by the Lyapunov method, and the effectiveness of the algorithm is verified by a simulation example. [ABSTRACT FROM AUTHOR]

• A new low-order integrated guidance and control model is proposed. • The fixed time integrated guidance and control scheme and related stability analysis. • The angle constraints of body line-of-sight and roll are considered. • The tracking performance for body line-of-sight angle is improved by a long way. Strap-down seeker is rigidly fixed onto the missile body, which results in detection information being coupled to the missile's attitude and having a narrow field-of-view (FOV). During the terminal guidance flight, attitude adjustment of the missile may lose the target's lock and reduce interception accuracy. Therefore, this paper investigates three-dimensional integrated guidance and control (IGC) under the constraints of the FOV and roll angle for skid-to-turn (STT) missile with strap-down seeker. A new low-order IGC model is constructed by establishing a second-order model of body line-of-sight (BLOS) angle based on strap-down decoupling theory and combining it with the second-order roll angle equation. Furthermore, a low-order fixed-time IGC scheme is developed using the integral barrier Lyapunov function (iBLF) to limit BLOS and roll angles. Fixed-time filter, which avoids the "complexity explosion" caused by conventional back-stepping technique, is utilized for obtaining virtual control command and its derivative. A fixed-time disturbance observer is introduced to compensate for the lumped disturbance. According to Lyapunov stability theory, it is proven that the proposed IGC scheme can make the closed-loop system converge within a fixed time. Finally, the effectiveness and robustness of the IGC scheme are verified by various numerical simulations. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of event-triggered integral sliding mode control (ISMC) for the perturbed nonlinear based-Takagi-Sugeno (TS) fuzzy systems. To reduce the chattering introduced by the unmatched disturbances, a disturbance observer is designed to get the estimated unmatched disturbances. To further reduce the computational burden and communication resources, compared with previous studies, two types of sliding surfaces are established. The time-triggered-based sliding surface which is used to ensure the reachability of the system states and the event-triggered-based sliding surface that is presented to calculate the control law, directly which benefits from less updates and consequently, less chattering that enhance the system performance. Moreover, the suggested control scheme is proposed based on asynchronous trait, i.e. , the premise variables of the controller are in different time scale with the fuzzy systems which also leads to communication resource reduction. As a key issue in event-triggered control, it is ensured that the proposed controlled system is Zeno-free along the implementation. By the Lyapunov theory, the appropriate conditions for the ultimate boundedness stability (UBS) of the closed-loop system with a prescribed H ∞ performance are derived in new offline LMIs. In order to illustrate the effectiveness of the suggested event-triggered integral sliding mode control, the Rossler system and track-trailer system are simulated and the obtained results are evaluated with the existing methods. [ABSTRACT FROM AUTHOR]

In this paper, a two-layer supervisory control scheme is proposed for discrete-time linear systems with state/input constraints, including multiple state time-delays, parametric uncertainties, and exogenous disturbance. The inner control layer is designed to achieve robust H ∞ tracking performance considering the delays as extra states but neglecting the input/state constraints. On the other hand, in the outer control layer, a command governor (CG) is designed to robustly guarantee the satisfaction of state and input constraints by computing a minimal Robust Positively Invariant (mRPI). To this end, the CG manipulates reference inputs by generating the nearest admissible value to be applied to the closed-loop system in both transient and steady-state response through the computation of the Maximal Output Admissible Set (MOAS). Finally, the validity of the proposed scheme is assessed in simulation using a numerical example and a continuous stirred tank reactor (CSTR) system. [ABSTRACT FROM AUTHOR]

This paper presents an additive-state-decomposition-based model predictive tracking control and disturbance rejection method for a permanent magnet synchronous motor (PMSM) servo system subject to unknown parameter perturbations, unmodeled dynamics, and time-varying load torque. The basic idea of this method is to equivalently decompose the original system into a primary system for handling the tracking control subproblem and a secondary system for dealing with the robust stabilization subproblem. A model predictive controller is designed for the primary system to achieve high-accuracy tracking of the reference speed. As for the secondary system, a novel high-order generalized extended state observer (HGESO) is constructed to estimate the multiple disturbances simultaneously, and a state feedback control law incorporating a disturbance compensator is developed to eliminate the adverse effect of the multiple disturbances on the system output. By combining the control inputs of the two subsystems together, the control objectives of the original system can be achieved. Both the stability criterion and design procedure of the closed-loop control system are developed. Finally, hardware-in-the-loop-based comparative experiments are conducted to demonstrate that the proposed method effectively suppresses the influence of the multiple disturbances on motor speed tracking accuracy and that the control system has both satisfactory dynamic performance and robustness. [ABSTRACT FROM AUTHOR]

This paper addresses the distributed control of delayed interconnected nonlinear systems with time-varying delays in both the local subsystems' dynamics and the physical interconnections among the subsystems. The Takagi–Sugeno fuzzy model with nonlinear consequent parts (N-TS), which is capable to provide less complex representations than standard T–S fuzzy models, is considered to efficiently deal with this class of complex systems. Then, based on Lyapunov–Krasovskii stability arguments, a synthesis condition is proposed to design a distributed control law such that the origin of the closed-loop interconnected system is locally asymptotically stable together with a guaranteed set of admissible initial conditions for which the validity of the N-TS fuzzy model is ensured. Moreover, a quasi-convex optimization procedure is formulated to enlarge the set of admissible initial conditions. The effectiveness of the proposed synthesis condition is validated in two numerical examples, including an interconnected power network with seven generators. [ABSTRACT FROM AUTHOR]

This paper investigates the robust output regulation problem for stochastic systems with additive noises. As is known, for the output regulation control problem, a general method is to regard that the system is disturbed by an autonomous exosystem (which is consisted by external disturbances and reference signals), and for the system disturbed by the white noise, the stochastic differential equations (SDEs) should be utilized in modeling, accordingly, a controller with a feedforward regulator is constructed for the stochastic system with an exosystem, which can not only cancel the external disturbance, but also transform the trajectory tracking problem into the stabilization problem; In consideration of the state variables in stochastic systems cannot be measured completely, we embed an observer to the controller, such that the random interference can be suppressed, and the trajectory tracking can be achieved. Based on the stochastic control theory, the criteria of the exponential practical stability in the mean square is presented for the closed-loop system, finally, through tuning the controller parameters, the mean square of the tracking error can converge to an arbitrarily small neighborhood of the origin. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of adaptive event-triggered (AET) based optimal fuzzy controller design for nonlinear networked control systems (NCSs) characterized by Takagi–Sugeno (T–S) fuzzy models. An improved AET communication scheme with a memory adaptive rule is proposed to enhance the utilization of the state response vertex data. Different from the existing ET based results, the improved AET scheme can save more communication resources and acquire better system performance. The sufficient criteria of performance analysis and controller design are presented for the closed-loop control system subject to mismatched membership functions (MFs) and AET scheme. And then, a new MFs online learning algorithm on the basis of the gradient descent approach is employed to optimize the MFs of fuzzy controller and obtain optimal fuzzy controller for further improving system performance. Finally, two simulation examples are presented to verify the advantage and effectiveness of the provided controller design technique. [ABSTRACT FROM AUTHOR]

This paper studies the adaptive tracking control problem for a class of uncertain high-order fully actuated (HOFA) systems with actuator faults and full-state constraints. Firstly, we design a novel nonlinear transformation function (NTF) only related to state and constraint boundaries and capable of handling asymmetric time-varying constraints. With the designed function, we obtain an equivalent totally unconstrained HOFA model which is generally simpler to design controllers than first-order state-space model. Then, the adaptive fault-tolerant controller is constructed with the help of the HOFA approach. By applying the Lyapunov stability theory, it is rigorously proved that the output tracking error converges to zero asymptotically, other signals of the resulting closed-loop systems are bounded, and full-state constraints are not violated for all time. Finally, the simulation results verify the efficiency of the proposed control design method. [ABSTRACT FROM AUTHOR]

We propose a robust observer-based output-feedback (OBOF) controller design method for the positive stabilization of discrete-time Takagi–Sugeno (T–S) fuzzy models subject to immeasurable premise variables, parametric uncertainties, and l ∞ disturbances. The results of this paper are as follows. First, a new fuzzy OBOF controller structure is used to improve the possibility that the uncertain closed-loop system is positive. Second, the separation principle is demonstrated for the l ∞ – l ∞ disturbance attenuation. Finally, the stability, positivity, and disturbance attenuation of T–S fuzzy closed-loop models are analyzed in the presence of the perturbation caused by the imperfect premise matching by the immeasurable premise variable. [ABSTRACT FROM AUTHOR]

In this paper, the dynamic event-based resilient consensus control of the multiple networked Euler-Lagrangian (E-L) systems under the Denial of Service (DoS) attacks is considered. Compared with linear cyber-physical systems, nonlinear networked E-L systems are more complex and closer to actual mechanical systems. For the situation where the topology is a strongly connected directed topology, a controller based on a dynamic event-trigger mechanism is designed to achieve consensus control for the networked E-L system in the absence of DoS attacks. Sufficient conditions are presented, which can guarantee the closed-loop system be stable. Then the resilient consensus problem of event-based controllers under energy-constrained DoS attacks is analyzed. The conditions related to the duration and frequency of DoS attacks are given. Zeno behavior is proved does not exist in the proposed control scheme. Finally, some numerical simulation results are given for verifying the theoretical results. [ABSTRACT FROM AUTHOR]

This paper studies model predictive security control (MPSC) for networked switched systems under denial-of-service (DoS) attacks. Most of existing works only adjust the triggering scheme when being attacked. Different from them, this paper proposes a novel timing-response event-triggering scheme (TR-ETS) to reduce the impact of attacks on system performance, which can not only configure system resources adaptively, but also accurately detect attack information and compensate the attacked data. Specifically, the proposed scheme includes two event-based triggers, which can dynamically and jointly regulate the communication/calculation ability, generate virtual attack sequences and acquire the number of passive packet loss. Then, based on the triggered states, a class of model predictive controllers is designed to optimize the control action. Due to possible strong attacks, a security control framework including network and local loops be introduced and a permissable type-switching mechanism (PTM) is used. Under the permissable controllers (i.e., network and local controllers), sufficient conditions for the stability of closed-loop switched systems are derived. In addition, a set of model predictive optimization algorithm using linear matrix inequalities (LMIs) technique is addressed. Finally, the effectiveness of the proposed method is verified by illustrative examples. [ABSTRACT FROM AUTHOR]

This paper develops a practical fixed-time bipartite consensus control framework for the uncertain nonlinear multi-agent systems (MASs) via using a barrier Lyapunov function (BLF)-based approach. Distinguish from the most existing results, the unknown nonlinearities of MASs in this paper are tackled by utilizing the robustness of BLF instead of applying fuzzy logic systems/neural networks approximating. In order to avoid feasibility verification in the traditional BLF method, a piecewise and differentiable function named the shift function is skillfully inserted into the coordination transformation of the controller design process, allowing not only the initial value of MASs states to be chosen arbitrarily, but also the settling time of bipartite consensus errors can be pre-designated. According to the backstepping framework, an approximated-free control algorithm is developed by combining the shift function with BLF, which guarantees that for any initial state of MASs, the outputs of all the agents can achieve the practical fixed-time bipartite consensus tracking, and all the signals in closed-loop systems are bounded. Especially, the settling time and the tracking error accuracy can be appointed by the designer. Finally, simulation results are given to show the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

This paper presents an innovative event-triggered fuzzy control approach for networked systems operating over unreliable network channels. Traditional complicated modeling and analysis process of network induced issues is replaced by a bran-new logarithmic quantization based event-triggered scheme method. The joint characterization of mixed data missing, arising from the event-triggered mechanism and unreliable network channels, becomes a challenging issue due to disrupted data sequences and variable relations. Consequently, this paper contributes a formulated auxiliary stochastic sequence approach to overcome the difficulty of dynamics modeling. With an formulated event driven controller, the modeling and implementation of the closed-loop systems are constructed and further simplified. Considering the difference and relation between the membership functions of plant and controller, we present a new fuzzy output feedback controller design method to obtain feasible result via uncertainty based method. Finally, we verify the validity of the designed control policy via a simulation example. [ABSTRACT FROM AUTHOR]

In this paper, a sliding mode sensor fault tolerant control scheme which involves a first order sliding mode observer, fault compensation logic and an integral sliding mode controller, is proposed for a class of uncertain linear parameter-varying systems. The proposed scheme has the capability to retain near nominal fault-free performance in the face of a class of sensor faults/failures. In particular, the closed-loop stability of the sensor fault tolerant scheme involving the sliding mode observer and the sliding mode controller in the presence of faults and uncertainty, is rigorously analysed. Furthermore, the paper proposes an algorithm to simultaneously synthesize the design freedom associated with the observer gains and control law despite the lack of a separation principle in the closed loop system overall caused by the uncertainty. The proposed scheme is validated using a commercial aircraft model. Good simulation results show the efficacy of the scheme. [ABSTRACT FROM AUTHOR]

This paper investigates the stabilization of a wave equation with uncertain boundary actuator dynamics. The remarkable characters of the system under investigation are revealed by the essential nonlinearities involved in the boundary actuator and the serious parametric unknowns coming from anti-damping coefficient at uncontrolled boundary and those in the actuator, which result into the incapability of the traditional control methods on this topic. For this, a novel adaptive control strategy is proposed in this paper. Specifically, a Riemann variables based state transformation is first introduced to change the original system into a new one whose stabilization implies that of the original system. Then, a state-feedback controller joint with some adaptive laws which are smartly chosen for the compensation of unknown parameters is explicitly designed by a finite-dimensional backstepping procedure. Owing to the compensation of boundary actuator dynamics, the performance analysis of the closed-loop system is more complicated than that of the related literature. For this, a rigorous recursive step is given to show the stability of the resulting closed-loop system. Finally, a numerical example is provided to verify the effectiveness of the proposed theoretical results. [ABSTRACT FROM AUTHOR]