Event-triggered-based Adaptive Output Feedback Control with Prescribed Performance for Strict-feedback Nonlinear Systems

Abstract

This paper mainly investigates the problem of event-triggered output feedback control for a class of strict feedback systems that satisfies a prescribed performance. With the help of introducing the prescribed performance functions, the constraint conditions on the tracking error can be obtained, which can converge to an arbitrarily small residual set, meanwhile the maximum overshoot is less than a pre-specified value. For the case of unmeasurable state, a state observer is used as approximation model to estimate them. Moreover, in order to reduce the computation burden, the event-triggering mechanism is successfully combined with backstepping. To guarantee the prescribed performance for tracking error and the boundedness property for all signals in the closed loop, an effective event-triggered adaptive output feedback control method is developed based on the relative threshold strategy, which needs to update only one parameter online. In simulation, the comparative results are provided to illustrate the validity of the control scheme.