Event-triggered adaptive optimal control using output feedback: An adaptive dynamic programming approach

Abstract

This paper proposes an event-triggered adaptive optimal output-feedback control method for continuous-time linear systems. With the proposed design, the unmeasurable states are reconstructed by using the measurable input and output data, and the discrete-time algebraic Riccati equation is iteratively solved through adaptive dynamic programming. Then, an event-based feedback strategy is introduced to the closed-loop system to reduce the communication between the controller and the plant. Convergence to the optimal solution and the closed-loop stability analysis are carried out by using Lyapunov method. Two numerical examples are employed to verify the effectiveness of the design.