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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]