Command Filtered Adaptive Fuzzy Event-Triggered Control for Stochastic Time-Delay Nonlinear System With Time-Varying Output Constraints

Xuejing Zhao, Junsheng Zhao, Zongyao Sun, Qi Xun Lan, Dengxiu Yu

Research output: Contribution to journalArticlepeer-review

Abstract

In this article, an adaptive fuzzy event-triggered tracking control strategy is proposed for stochastic time-delay nonlinear systems with time-varying output constraints based on command filtered technology. First, we combine a barrier Lyapunov function with the backstepping method to deal with the time-varying asymmetric output constraints. Simultaneously, the Lyapunov–Krasovskii functional is employed to compensate for the effect of time-delay. Second, a command filtered technique is introduced to address the “explosion of complexity” issue caused by the backstepping process. Furthermore, an error compensation mechanism is established to mitigate the effects of the error generated by the command filter. Subsequently, the universal approximation capability of the fuzzy logic system is utilized to handle the system's unknown nonlinear terms. Notably, the design of the event-triggered mechanism is effective in significantly reducing the communication burden and enhancing resource utilization. The presented control scheme not only guarantees that all signals in the closed-loop system are semi-globally uniformly ultimately bounded but also remains free of Zeno behavior without violating the output constraints. Finally, two simulation examples validate the feasibility of the scheme.

Original languageEnglish
Pages (from-to)3411-3423
Number of pages13
JournalInternational Journal of Robust and Nonlinear Control
Volume35
Issue number9
DOIs
StatePublished - Jun 2025

Keywords

  • adaptive fuzzy control
  • command filter
  • event-triggered mechanism
  • stochastic time-delay nonlinear systems

Fingerprint

Dive into the research topics of 'Command Filtered Adaptive Fuzzy Event-Triggered Control for Stochastic Time-Delay Nonlinear System With Time-Varying Output Constraints'. Together they form a unique fingerprint.

Cite this