Event-triggered-based adaptive asymptotic tracking control for stochastic nonlinear time-delay systems with actuator and sensor faults

The issue of dynamic event-triggered adaptive asymptotic tracking control for stochastic nonlinear time-delay systems with actuator and sensor faults is investigated in this article. Utilizing fuzzy logic systems and projection operator, unknown time delays are calculated. Compared with the existing methods to overcome the effect of time delay, the estimation of the time delay information is considered to avoid the controller singularity problem. Moreover, to reckon the upper bound of fuzzy logic system approximation errors and other residuals, an error adaptive law is developed in the controller construction. With the assistance of stochastic Barbalat’s lemma and adaptive fuzzy control strategy, a novel asymptotic tracking fuzzy controller is proposed under multiple faults, which guarantees that the whole signals are bounded in probability. Besides, a dynamic event triggering control (DETC) is employed to save the communication resources. A practical example is supplied to demonstrate the effectiveness of the proposed control approach.