Finite-horizon optimal control design for uncertain linear discrete-time systems

In this paper, the finite-horizon optimal adaptive control design for linear discrete-time systems with unknown system dynamics by using adaptive dynamic programming (ADP) is presented. In the presence of full state feedback, the terminal state constraint is incorporated in solving the optimal feedback control via the Bellman equation. The optimal regulation of the uncertain linear system is solved in a forward-in-time and online manner without using value and/or policy iterations. Due to the nature of finite horizon, the stability of the closed-loop system is involved but verified by using Lyapunov theory. The effectiveness of the proposed method is verified by simulation results.

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