Dynamic event-triggered adaptive tracking control improves output in stochastic systems with unknown time delays, highlighting effective fuzzy approximation methods.
Abstract This paper concentrates upon the dynamic event-triggered adaptive tracking control for nonstrict-feedback stochastic nonlinear systems with unknown time delays and deferred output constraint (DOC). With the assistance of fuzzy approximation and projection operator, unknown time delays are calculated. In addition, the ingenious application of inequality can avoid the infinite high-frequency switching of the control laws. Furthermore, an error adaptive law is introduced to reckon the upper bound of fuzzy approximation errors and other residuals. By developing estimation of time delays and error adaptive laws, a dynamic event-triggered adaptive fuzzy control scheme is obtained such that the whole signals are bounded in probability. The system output satisfies the deferred output constraint and the tracking error converges to the prescribed boundary at a specified time. A simulation example is supplied to verify the effectiveness of the proposed control scheme.
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Zhang et al. (2025) studied this question.
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