Title :
Linear optimal tracking control: An adaptive dynamic programming approach
Author :
Weinan Gao ; Zhong-Ping Jiang
Author_Institution :
Dept. of Electr. & Comput. Eng., New York Univ., New York, NY, USA
Abstract :
This paper addresses the optimal output regulation problem of linear systems with unknown system dynamics. The exogenous signal is presumed to be generated by a continuous-time linear exosystem. Firstly, we formulate the linear optimal output regulation problem (LOORP). Then, we give an offline solution of LOORP to design the optimal static state-feedback servoregulator by solving an algebraic Riccati equation (ARE) and a regulator equation. Instead of solving these two equations directly, by using state, input and exogenous signals collected online, we employ an approximate/adaptive dynamic programming (ADP) technique to seek online approximations of above equations whereby we get the approximated optimal servoregulator. Rigorous stability analysis shows that the closed-loop linear system is exponentially stable. Also, the output of the plant asymptotically tracks the given reference. Simulation results demonstrate the effectiveness of the proposed approach.
Keywords :
Riccati equations; adaptive control; approximation theory; asymptotic stability; continuous time systems; control system synthesis; dynamic programming; linear systems; optimal control; servomechanisms; state feedback; ADP technique; ARE; LOORP; adaptive dynamic programming approach; adaptive dynamic programming technique; algebraic Riccati equation; approximate dynamic programming technique; approximated optimal servoregulator; closed-loop linear system; continuous-time linear exosystem; exogenous signal; exponential stability; linear optimal output regulation problem; linear optimal tracking control; linear systems; online approximations; optimal output regulation problem; optimal static state-feedback servoregulator design; regulator equation; unknown system dynamics; Adaptive systems; Convergence; Dynamic programming; Linear systems; Mathematical model; Regulators; System dynamics;
Conference_Titel :
American Control Conference (ACC), 2015
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4799-8685-9
DOI :
10.1109/ACC.2015.7172106