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Event-triggered fixed-time adaptive fuzzy control for state-constrained stochastic nonlinear systems without feasibility conditions

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Abstract

The problem of event-triggered fixed-time control for state-constrained stochastic nonlinear systems is discussed in this article. Different from the barrier Lyapunov function (BLF)-based and Integral BLF-based schemes that rely on feasibility conditions (FCs), by introducing the nonlinear state-dependent functions, the asymmetric time-varying state constraints are handled without FCs. Combined with the fixed-time stability theory and the dynamic surface control technique with fixed-time filter, the fixed-time stability in probability of the closed-loop system is ensured and the problems of “explosion of complexity” and “singularity” are overcome. Furthermore, the novel fixed-time error compensation signals are designed to compensate the filtering errors, and the event-triggered control technique is used to save network resources. Simulations also illustrate the effectiveness of the proposed method.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (61603003, 61472466).

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Authors and Affiliations

  1. School of Mathematics, Hefei University of Technology, Hefei, 230601, China

    Yangang Yao, Jieqing Tan & Xu Zhang

  2. School of Computer and Information, Anqing Normal University, Anqing, 246011, China

    Jian Wu

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Yao, Y., Tan, J., Wu, J. et al. Event-triggered fixed-time adaptive fuzzy control for state-constrained stochastic nonlinear systems without feasibility conditions. Nonlinear Dyn 105, 403–416 (2021). https://doi.org/10.1007/s11071-021-06633-7

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