Adaptive event-triggered output-feedback controller for uncertain nonlinear systems

This paper addresses the event-triggered output-feedback stabilization for a class of uncertain nonlinear systems. Essentially different from the related literature, the systems under investigation allow large uncertainties (whose size is unknown) coupling to unmeasurable states, which requires to integrate a comprehensive output-feedback compensation mechanism into the event-triggered philosophy and would bring substantial challenges to the event-triggered control. To solve the problem, a novel scheme of adaptive event-triggered output-feedback control is established for the systems. Specifically, an adaptive dynamic gain is introduced not only to counteract the large uncertainties but also to cope with the execution/sampling error. Then, an adaptive event-triggered output-feedback controller based on dynamic-gain observer is constructed to guarantee global convergence for the resulting closed-loop system while reducing execution/sampling. Particularly, the event-triggering mechanism involved is delicately designed by fully exploiting the dynamic gain, to enable the negative influence of the gain through the execution error to be counteracted (no matter how large the gain becomes) while precluding infinitely fast execution which violates the implementation of event-triggered controller in practice. Correspondingly, a distinctive analysis pattern is implemented for the closed-loop performance, due to the coupling of the dynamic-gain compensation mechanism and the event-triggering mechanism. Moreover, for more efficient resource saving, we further show the feasibility of adaptive dynamic event-triggering mechanism for the desired stabilization. (C) 2020 Elsevier Ltd. All rights reserved.