Dynamic event-triggered adaptive optimal control for linear discrete time-varying systems

Abstract

Given the excessive consumption of communication resources in time-varying systems without prior system information, efficient resource-saving strategies are of vital importance. This paper explores and analyzes the event-triggered adaptive the control issue concerning linear discrete systems with time-varying characteristics. Without relying on prior system knowledge, a dynamic event-based triggering mechanism is established to reduce computation and communication costs. By using available input and state data, a dynamic event-driven adaptive optimal control strategy is designed. Based on the Lyapunov stability theory, a rigorous stability analysis is conducted, and the conditions for achieving asymptotic stability of the closed-loop system are given. To conclude, numerical results confirm that the developed method works well. Meanwhile, the communication frequency between the controller and the controlled plant is reduced by 66 percent, the closed-loop stability is ensured, and the computational and communication resources are efficiently conserved.