Adaptive Intelligent Control for Nonlinear Strict-Feedback Systems With Virtual Control Coefficients and Uncertain Disturbances Based on Event-Triggered Mechanism

This paper investigates the problem of adaptive fuzzy control on the basis of an event-triggered mechanism for nonlinear strict-feedback systems with time-varying external disturbances and virtual control coefficients in the presence of actuator failures. Virtual control coefficients are correlated with the designed adaptive law and control signal. In the backstepping technique procedure, fuzzy logic systems are utilized to approximate an unknown nonlinear function, and the tuning function is implemented to cope with the destabilizing problem of the control design. To save communication resources, an adaptive fuzzy event-triggered control strategy is developed to update the control input when the triggering condition is satisfied. Then, all of the closed-loop signals can remain semi-globally uniformly ultimately bounded. The Zeno behavior can be excluded. Finally, a numerical example and a real system are provided to illustrate the effectiveness of the proposed approach.