DocumentCode
728579
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
fYear
2015
fDate
1-3 July 2015
Firstpage
4929
Lastpage
4934
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;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference (ACC), 2015
Conference_Location
Chicago, IL
Print_ISBN
978-1-4799-8685-9
Type
conf
DOI
10.1109/ACC.2015.7172106
Filename
7172106
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