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This article investigates the event-based distributed fuzzy load frequency control approach for nonlinear interconnected power systems under a switching topology. Specifically, nonlinear factors and uncertain parameters existing in turbine and governor dynamics are modeled and analyzed under the interval type-2 fuzzy method. New memory-based adaptive event-triggered mechanisms, whose directions and threshold parameters are dynamically updated based on the output change trend and relative output error of multiple memories, are proposed to further save network energy. Aiming at communication topology changes in multiarea power systems, a novel switched control system is established by introducing a time-varying communication matrix. Then, the system’s asymptotic stability is ensured by the piecewise Lyapunov–Krasovskii method. Furthermore, to further relax stability conditions, slack matrices are considered with the boundary information of membership functions. Finally, three-area power systems are shown to demonstrate the effectiveness of proposed distributed load frequency control strategies. [ABSTRACT FROM AUTHOR]

This article studies the event-based adaptive practical fixed-time decentralized control problem for a class of large-scale uncertain nonlinear systems subject to non-affine nonlinear faults. By fusing the techniques of fixed-time control and command filter, the problems such as singular-value and computational explosion in fixed-time control based on backstepping design framework are solved. Based on the fuzzy approximation theory and Butterworth low-pass filter (BLPF) technique, the non-affine nonlinear fault terms are processed and fault-tolerant controllers are designed to realize fault compensation. In order to relieve the communication the pressure between system components, a novel switching event-triggering mechanism (SETM) based on user-set threshold parameters is proposed. This switching threshold design the scheme combines the advantages of the traditional fixed threshold and relative threshold design strategies, providing greater flexibility in balancing system performance and network constraints. By combining the practical fixed-time stability criterion with the Lyapunov stability theory, it is demonstrated that both the tracking performance and the closed-loop stability can be ensured in a fixed-time. Finally, two simulation examples are given to verify the effectiveness of the proposed fixed-time switching event-triggered control (SETC) scheme. [ABSTRACT FROM AUTHOR]

This article investigates the fault-tolerant fixed-time cooperative control problem for nonstrict-feedback nonlinear multiagent systems subject to error constraints and input saturation. Fuzzy logic systems are employed to deal with unknown nonlinear dynamics. By using adaptive technique and power integration technique, two barrier-function-based fixed-time control strategies are projected. In the first scheme, a novel adaptive fault-tolerant distributed fixed-time control protocol is developed. Besides, a new real-time compensation mechanism is proposed, where the compensation signal is provided if and only if there exists input saturation. Compared with the mechanisms for always compensating signals in existing results, the proposed real-time compensation mechanism may reduce energy consumption. In the second scheme, an adaptive fault-tolerant priority-based fixed-time control protocol is proposed, which may reduce the computational complexity arising from numerous neighbors’ variables. Both of the proposed two strategies can avoid the singular problem by constructing high-order derivable continuous functions. Besides, the developed control protocols can ensure the errors in MASs are practical fixed-time stable, meanwhile, the error constraints will not be violated in operation. Stability analysis and simulation results illustrate the effectiveness of the proposed strategies. [ABSTRACT FROM AUTHOR]

This paper investigates the problems of decentralized adaptive neural network (NN) secure control for a class of nonstrict-feedback nonlinear interconnected large-scale systems (NILSs) under denial-of-service (DoS) attacks. The considered systems contain not only unknown interconnected terms but also general nonlinear functions that are not required to be globally Lipschitz, in contrast to most of the existing results in the area. When the system subject to the DoS attack, the sampled data can neither be sent by the sensors nor received by the actuators due to the appearance of DoS in the sensor-to-controller (S-C) and the controller-to-actuator (C-A) communication channels. The data packets sent from the sensors are blocked and the traditional backstepping technology cannot be adopted. In order to solve this difficulty, a novel dynamic gain observer is constructed, which can obtain the desired states from the NILSs under DoS attacks. Considering the energy limitation of attackers, two reasonable Assumptions of DoS attack intensity are given. The stability is proven based on the Lyapunov stability theory (LST) and the improved average dwell time (ADT) method. The proposed controller guarantees that all signals in closed-loop systems are bounded, while the tracking error signals converge to a small residual set. Finally, two simulation examples are provided to illustrate the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

This article investigates the asynchronous adaptive event-triggered control problem for networked interval type-2 (IT2) fuzzy systems subject to nonperiodic denial-of-service (DoS) attacks. Unlike some existing results, two resilient adaptive event-triggered mechanisms (AETMs) are applied independently to both sensor and controller output while resisting nonperiodic DoS attacks. In particular, the asynchronous resilient AETM thresholds are adaptively varied based on error information between current sampling and latest available packets. Then, a new switched IT2 fuzzy dynamical output feedback system is modeled by discussing the influence of the AETM and nonperiodic DoS attacks simultaneously. Furthermore, mismatched membership functions are considered between dynamic output feedback controller and IT2 fuzzy model, and a slack matrix is introduced to relax stability conditions. Besides, by utilizing the piecewise Lyapunov–Krasovskii function method, sufficient conditions are derived to guarantee that the newly constructed switching system is globally exponentially stable with $H_{\infty }$ performance. Finally, the effectiveness of the developed control approach is illustrated by two examples. [ABSTRACT FROM AUTHOR]

Summary: In this article, an adaptive fuzzy output feedback control method is presented for nonlinear time‐delay systems with time‐varying full state constraints and input saturation. To overcome the problem of time‐varying constraints, the integral barrier Lyapunov functions (IBLFs) integrating with dynamic surface control (DSC) are applied for the first time to keep the state from violating constraints. The effects of unknown time delays can be removed by using designed Lyapunov‐Krasovskii functions (LKFs). An auxiliary design system is introduced to solve the problem of input saturation. The unknown nonlinear functions are approximated by the fuzzy logic systems (FLS), and the unmeasured states are estimated by a designed fuzzy observer. The novel controller can guarantee that all signals remain semiglobally uniformly ultimately bounded and satisfactory tracking performance is achieved. Finally, two simulation examples illustrate the effectiveness of the presented control methods. [ABSTRACT FROM AUTHOR]

• The DOS attacks is first considered in the heterogeneous nonlinear multi-agent systems in this paper. • By designing a control strategy and using impulsive theorem, some conditions are derived to achieve quasi-synchronization. • The relationship among control strength, impulsive interval and attacks strength is analyzed with two impulsive effects. • The average impulsive interval is considered to unify the synchronization criteria of systems with two impulsive effects. This paper is concerned with the quasi-synchronization of heterogeneous nonlinear multi-agent systems under DOS attacks with impulsive effects. The impulsive effects play either a positive role (impulsive control) or a negative role (impulsive disturbance) in the synchronization problem. The communication topology subjected to DOS attacks is considered, which destroys the communication channel among agents. A connectivity restoration mechanism is assumed. Only considering the positive impulsive effect, the controller does not need to operate constantly, which will reduce the controller resource consumption. Only taking the negative impulsive effect into account, a feedback controller is designed to counteract with the impulsive disturbance and DOS attacks. By using the concept of 'average impulsive interval', the criterion of quasi-synchronization with two impulsive effects is unified. Based on the impulsive theorem, the relationship among attack strength, control gain and average impulsive interval is analyzed. The results are illustrated by a simulation example. [ABSTRACT FROM AUTHOR]

Highlights • The ADP algorithm of actor-critic networks is used to deal with the decentralized reliable guaranteed cost control problem of large-scale nonlinear systems with mismatched interconnection and time-varying actuator fault. • A novel relationship of the control policy between isolated system and original system with interconnection and actuator faults, is constructed. • The considered reliable guaranteed cost control problem is transformed into design an optimal control strategy of the isolated system. Abstract In this paper, the decentralized reliable guaranteed cost control problem of large-scale nonlinear systems with mismatched interconnection and time-varying actuator fault is investigated. The unknown actuator fault is assumed to be with known upper bounds. Under the case that the interconnection term is unknown and mismatched, the guaranteed cost control problem for a class of large-scale nonlinear systems can be transformed into design an optimal control strategy of the isolated system, which is necessary to solve the HJB (Hamilton–Jacobi–Bellman) equations by using adaptive dynamic programming (ADP) of actor-critic networks. The convergence property of the neural network weights and the stability of the closed-loop system have been strictly proved even if time-varying actuator faults and unknown interconnection coexist. Finally, simulation examples are given to show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Summary: This paper concerns the fixed‐time stabilization problem for uncertain strict‐feedback nonlinear systems. Generally, the so‐called fixed‐time stabilization is an extended concept of global finite‐time stabilization. By using fixed‐time controller, the convergence time of the closed‐loop system can be pre‐set by adjusting design parameters, which has more practical application values. The idea of bi‐limit homogeneity has been introduced to design the fixed‐time controller with two terms, whose orders are tuning by a bi‐limit–like strategy. That is the orders of the two terms are less than 1 and more than 1, respectively. Meanwhile, by utilizing power integral terms in the controller, the problem arising from the growth rates of uncertain nonlinear functions can also be solved. Based on appropriate Lyapunov function and backstepping technology, the parameters of the controller are finally determined, and the developed controller ensures the stabilization of system within a fixed time. Stability analysis and simulation results are respectively given to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper studies the fault-tolerant control problem for a class of nonlinear systems based on polynomial fuzzy model. A typical actuator fault model is presented to describe the loss of effectiveness fault in a multimode framework. The considered polynomial-fuzzy-model-based systems are more general, since the assumption that the input matrix \mathbf Bi(\mathbf {x}),i=1,\ldots, p has at least one zero row, is not required any more. A polynomial Lyapunov function candidate depending on any system state is applied to design the fault-tolerant controller, in which the number of rules and membership functions can be matched or mismatched with polynomial fuzzy model. To deal with nonconvex problem, some nonlinear terms are successfully described as an index to be optimized to zero by a semidefinite programming. Compared with some published works, the resultant sum of squares based design conditions are with less computation complexity and potentially more relaxed. Using the third-party MATLAB toolbox SOSTOOLS, simulation examples are given to illustrate the effectiveness of the new method. [ABSTRACT FROM PUBLISHER]

This paper investigates the fault detection and isolation (FDI) problem for a class of nonlinear systems with sensor outage faults. The considered nonlinear systems are described as affine fuzzy models, and the system outputs are chosen as the premise variables of fuzzy models. Different from the existing results, the influence of sensor faults on premise variables is considered. As a result, the well-known parallel distributed compensation scheme cannot be used for FDI filters design. By using the structural information encoded in the fuzzy rules, the affine fuzzy system is represented by multiple operating-regime-based models in fault-free case and faulty cases. In the multiple-model scheme, a bank of piecewise FDI filters are constructed, each of them is based on the affine fuzzy model that describes the system in the presence of a specified fault. The fault-dependent residual signals generated from the filters are used for detecting and isolating the specified fault. The FDI filter design conditions are obtained in the formulation of linear matrix inequalities. Finally, a numerical example is given to illustrate the effectiveness and merits of the proposed method. [ABSTRACT FROM PUBLISHER]

This paper is devoted to the control of Markov jump nonlinear systems with general transition probabilities (TPs) allowed to be known, uncertain, and unknown. With the help of the S-procedure to dispose the system nonlinearities and the TP property to eliminate the coupling between unknown TP and Lyapunov variable, an extended bounded real lemma for the considered system to be stochastically stable with the prescribed \mathcal H{\infty } performance is established in the framework of linear matrix inequalities. To handle the nonlinearity incurred by uncertain TP for controller synthesis, a separated method is proposed to decouple the interconnection between Lyapunov variables and controller gains. A numerical example is given to show the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

A novel decentralized adaptive integral sliding mode control law is proposed for a class of nonlinear uncertain large-scale systems subject to quantization mismatch between quantizer sensitivity parameters. Firstly, by applying linear matrix inequality techniques, integral-type sliding surface functions are derived for ensuring the stability of the whole sliding mode dynamics and obtaining the prescribed bounded L2 gain performance. Secondly, the decentralized adaptive sliding mode control law is developed to ensure the reachability of the sliding manifolds in the presence of quantization mismatch, interconnected model uncertainties, and external disturbances. Finally, an example is shown to verify the validity of theoretical results. [ABSTRACT FROM AUTHOR]

Abstract: This paper addresses the state feedback control of nonlinear continuous-time, Markovian-jump systems. The nonlinearity is represented by Takagi–Sugeno fuzzy models and the transition probability matrix is assumed to be partly known: some elements in the matrix are known, some are unknown but with known lower and upper bounds, and some are completely unknown. By making full use of the continuous property of the transition probability matrix, new sufficient conditions for the stochastic stability of the system are obtained in terms of linear matrix inequalities. We show that the conditions given are less conservative than or at least the same as those for existing results. Moreover, using the conditions obtained, we establish a method for design of a state feedback controller. Numerical examples illustrate the effectiveness of the proposed method. [Copyright &y& Elsevier]

In this paper, we investigate the time-varying formation tracking control (TVFTC) problem for high-order uncertain nonlinear multi-agent systems (MASs) with a dynamic leader. Both unknown disturbances and uncertain nonlinear functions are considered. A novel fixed-time TVFTC strategy is proposed with two steps, which can avoid the communication loop problem. Firstly, a distributed fixed-time observer (DFTO) for the directed graph is introduced, such that the leader's information can be accurately obtained by each agent within a bounded time. Secondly, by using fixed-time technique, a Lyapunov-function-based design process has been schemed to avoid the singularity problem. The developed TVFTC protocols can ensure all the followers achieve the desired time-varying formation and track the leader simultaneously. Furthermore, according to practical requirements, the configuration of formation can be chosen as arbitrary shape and the corresponding convergence time is allowed to be pre-estimated or preset. Stability analysis and some simulation examples for the control strategy are given, which further verify the validity. [ABSTRACT FROM AUTHOR]