Dual-channel event-triggered asymptotic tracking control of nonlinear systems with unmeasurable states

In this article, we study an event-triggered asymptotic tracking control problem for a class of networked nonlinear systems with unmeasurable states. In contrast to the majority of existing event-triggered control results, where only the input or output signal is triggered, the design problem of a dual-channel event-triggered mechanism is studied to achieve a more comprehensive saving of communication resources. Subsequently, in order to reconstruct system states, a continuous-discrete observer that can achieve asymptotic convergence of estimation errors is constructed based on event-triggered output. Then, an event-triggered asymptotic tracking control scheme is introduced through Levant differentiators, filtered error compensation signals, and the backstepping technique. The Levant differentiators not only address the challenge of computational complexity explosion but also effectively resolve the problem of controller segmentation continuity. The control scheme has been proven to maintain all signals in the closed-loop system bounded and achieve zero tracking error as time approaches infinity. Subsequently, numerical simulations are conducted to verify the effectiveness of the proposed approach.