Adaptive fuzzy control for non‐strict‐feedback stochastic uncertain non‐linear systems based on event‐triggered strategy

Abstract

This paper investigates the issue of adaptive fuzzy control for a category of non-strictfeedback stochastic uncertain non-linear systems. Based on event-triggered mechanism, an adaptive fuzzy controller with a simple form is designed by combining backstepping technique with fuzzy logic system. The devised controller not only ensures the output signal tracking reference signal and all signals of the closed-loop system are bounded in probability but also reduces the communication load between controller and actuator. In addition, the feasibility of the considered event-triggered mechanism is guaranteed by eliminating Zeno behaviour. Finally, the validity of the proposed result is proved by an example. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Dynamic Event-Triggered Adaptive Tracking Control for a Class of Unknown Stochastic Nonlinear Strict-Feedback Systems

“…Compared with time-triggered mechanisms, an event-triggered mechanism (ETM) can reduce the amount of data transmission more effectively, decrease the network load, and have higher flexibility. Thus, scholars have turned their attention to the study of ETM [1][2][3][4][5][6][7][8][9][10][11][12][13][14].…”

“…For uncertain nonlinear systems [5,6], Xing et al put forward three different ETMs through the adaptive backstepping design method. In [11,12], the authors consider the tracking control problem of stochastic nonlinear systems with an uncertain term. Two adaptive event-triggered controllers with fixed threshold and relative threshold are designed based on fuzzy logic system.…”

“…(2) An adaptive controller with DETM is designed for unknown stochastic nonlinear strict-feedback systems. Compared with SETM designed in [11,12], DETM can save more resources.…”