Adaptive Fuzzy Event-Triggered Control for Stochastic Nonlinear Systems With Full State Constraints and Actuator Faults

Ma, Hui; Li, Hongyi; Liang, Hongjing; Dong, Guowei

doi:10.1109/tfuzz.2019.2896843

Cited by 251 publications

(95 citation statements)

References 40 publications

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“…Remark 1. Compared with the previous result [44], the main property of the system (1) is that the unknown nonlinear function f i (•) includes the unknown time-varying periodically disturbance w i (t).…”

Section: Introductionmentioning

confidence: 88%

Adaptive event-triggered control for a class of nonlinear systems with periodic disturbances

et al. 2020

Sci. China Inf. Sci.

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246

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This paper investigates the adaptive event-triggered control problem for a class of nonlinear systems subject to periodic disturbances. To reduce the communication burden, a reliable relative threshold strategy is proposed. Fourier series expansion and radial basis function neural network are combined into a function approximator to model suitable time-varying disturbed function of known periods in strict-feedback systems. By combining the Lyapunov stability theory and the backstepping technique, the proposed adaptive control approach ensures that all the signals in the closed-loop system are bounded, and the tracking error can be regulated to a compact set around zero in finite time. Finally, simulation results are presented to verify the effectiveness of the theoretical results.

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Section: Introductionmentioning

confidence: 88%

Adaptive event-triggered control for a class of nonlinear systems with periodic disturbances

et al. 2020

Sci. China Inf. Sci.

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246

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“…Concentrating the problem on switched nonlinear systems, the authors in Reference 51 provided a finite‐time FTC scheme against arbitrary switching signals. FTC method with fast transient performance was investigated in Reference 52, which further provided a control strategy against full‐state constraints and event‐triggered mechanism.…”

Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy finite‐time fault‐tolerant control of nonlinear systems with state constraints and input quantization

Pan

Yang

et al. 2020

Adaptive Control & Signal

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Summary This article concentrates on an adaptive finite‐time fault‐tolerant fuzzy tracking control problem for nonstrict feedback nonlinear systems with input quantization and full‐state constraints. By utilizing the fuzzy logic systems and less adjustable parameters method, the unknown nonlinear functions are addressed in each step process. In addition, a dynamic surface control technique combined with fuzzy control is introduced to tackle the variable separation problem. The problem for the effect of quantization and unlimited number of actuator faults is tackled by a damping term with smooth function in the intermediate control law. Finite‐time stability is achieved by combining barrier Lyapunov functions and backstepping method. The finite‐time controller is designed such that all the responses of the systems are semiglobal practical finite‐time stable and ensured to remain in the predefined compact sets while tracking error converges to a small neighborhood of the origin in finite time. Finally, simulation examples are utilized to testify the validity of the investigated strategy.

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“…Different from the traditional time‐triggered mechanism, where the output of traditional periodic sampling controller was employed in the system regardless of whether the system needs it or not, the idea of the event‐triggered control method is triggered only when the systems need, therefore, it can lead to great reduction of the communication burden and the resources wasting. Therefore, the study of event‐triggered control for nonlinear systems has also received much attention from researchers 30‐38 . In some details, A small‐gain approach was proposed to deal with the input‐to‐state stability (ISS) and robust event‐triggered control for nonlinear systems with respect to measurement errors in Reference 31.…”

Section: Introductionmentioning

confidence: 99%

“…In some details, A small‐gain approach was proposed to deal with the input‐to‐state stability (ISS) and robust event‐triggered control for nonlinear systems with respect to measurement errors in Reference 31. Some effective controller design methods for nonlinear systems by combining event‐triggered mechanisms with virtual control law were demonstrated in the literature 32‐38 …”

Section: Introductionmentioning

confidence: 99%

Command filter‐based event‐triggered adaptive neural network control for uncertain nonlinear time‐delay systems

Bao-min

Xia

Sun

et al. 2020

Intl J Robust & Nonlinear

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In this article, the problem of command filter-based adaptive event-triggered neural network control is considered for a class of uncertain nonlinear systems with time delay. Lyapunov-Krasovskii functionals and command filtered technology are utilized to address the problem of unknown time-varying delays and explosion of complexity, respectively. Furthermore, by fusing the event-triggered mechanism, an adaptive tracking controller is designed. The proposed controller not only ensures that the system output eventually follows the desired reference signal in the sufficiently small neighborhood of zero but also reduces the communication resources from the controller to the actuator. Finally, the effectiveness of the proposed control method is verified by a simulation example.

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Adaptive Fuzzy Event-Triggered Control for Stochastic Nonlinear Systems With Full State Constraints and Actuator Faults

Cited by 251 publications

References 40 publications

Adaptive event-triggered control for a class of nonlinear systems with periodic disturbances

Adaptive event-triggered control for a class of nonlinear systems with periodic disturbances

Adaptive fuzzy finite‐time fault‐tolerant control of nonlinear systems with state constraints and input quantization

Command filter‐based event‐triggered adaptive neural network control for uncertain nonlinear time‐delay systems

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