Adaptive output-feedback optimal control for continuous-time linear systems based on adaptive dynamic programming approach

This paper investigates the adaptive output-feedback optimal control problem for a class of continuous time (CT) linear systems with dynamic uncertainties. Data-based controller design algorithm with policy iteration form is developed through adaptive dynamic programming (ADP) technique. In the process of proposed algorithm, only measured input and output information of the system is used to learn optimal control gain, but the exactly knowledge of the system is not required. Different from the existing works, the adaptive controllers learned by the algorithm has certain robustness to the dynamic uncertainties. Three examples are given to test the effectiveness and feasibility of the proposed approach. ? 2021 Elsevier B.V. All rights reserved.

Automated summary

This paper investigates an adaptive output-feedback optimal control problem for a class of continuous time (CT) linear systems with dynamic uncertainties. An algorithm based on adaptive dynamic programming (ADP) technique is proposed for data-based controller design, which only uses measured input and output information to learn optimal control gain without requiring exact system knowledge. The adaptive controllers learned by the algorithm exhibit robustness to dynamic uncertainties, as demonstrated through three examples.