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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]

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]