Finite-time command filtered event-triggered adaptive output feedback control for nonlinear systems with unknown dead-zone constraints

Abstract

This paper addresses the design of neural network observer and adaptive finite-time tracking controller for uncertain nonlinear with event-triggered inputs and unknown dead-zone constraints. To shorten the convergence time and reduce the computational burden, the finite-time command filter backstepping (CFB) technique is modified by improving the error compensation term, and a novel adaptive output feedback event triggering mechanism is developed in this way. It is proven that the newly presented control strategy achieves the goal of finite-time convergence and effectively saves network bandwidth. Meanwhile, all of the closed-loop signals are bounded, and the tracking performance is guaranteed based on the finite-time CFB method avoiding the problem of complexity explosion. Finally, a practical example is included to verify the validity of the proposed theoretical results.