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Event-triggered robust fuzzy adaptive control for non-strict feedback nonlinear system with prescribed performance

Author

Listed:
  • Sui, Shuai
  • Yu, Yuelei
  • Tong, Shaocheng
  • Philip Chen, C.L.

Abstract

This paper addresses a class of uncertain non-strict feedback nonlinear systems and proposes an event-triggered fuzzy adaptive prescribed performance control (PPC) strategy. Fuzzy logic systems (FLSs) are employed to approximate unknown smooth functions. In the control design, an event-triggered mechanism (ETM) from sensor-to-controller is introduced to economize on unnecessary transmission and communication resources. Additionally, a novel performance function is constructed to bound tracking errors, and a series of error transformations are devised to convert the “constrained” system into an equivalent “unconstrained” system. The proposed control strategy ensures that all signals in the closed-loop system have semi-globally uniformly bounded stability. Moreover, prescribed performance bounds ensure output tracking with minimal (or even zero) overshoot. Finally, the effectiveness and practicality of the proposed control method are validated through comparative simulations.

Suggested Citation

  • Sui, Shuai & Yu, Yuelei & Tong, Shaocheng & Philip Chen, C.L., 2024. "Event-triggered robust fuzzy adaptive control for non-strict feedback nonlinear system with prescribed performance," Applied Mathematics and Computation, Elsevier, vol. 474(C).
  • Handle: RePEc:eee:apmaco:v:474:y:2024:i:c:s0096300324001735
    DOI: 10.1016/j.amc.2024.128701
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