DocumentCode
592159
Title
Optimal adaptive controller scheme for uncertain quantized linear discrete-time system
Author
Qiming Zhao ; Hao Xu ; Jagannathan, Sarangapani
Author_Institution
Dept. of Electr. & Comput. Eng., Missouri Univ. of Sci. & Technol., Rolla, MO, USA
fYear
2012
fDate
10-13 Dec. 2012
Firstpage
6132
Lastpage
6137
Abstract
In this paper, the Bellman equation is used to solve the optimal adaptive control of quantized linear discrete-time system with unknown dynamics. To mitigate the effect of the quantization errors, the dynamics of the quantization error bound and an update law for tuning the range of the dynamic quantizer are derived. Subsequently, by using adaptive dynamic programming technique, the infinite horizon optimal regulation problem of the uncertain quantized linear discrete-time system is solved in a forward-in-time manner without using value and/or policy iterations. The asymptotic stability of the closed-loop system is verified by standard Lyapunov stability approach in the presence of state and input quantizers. The effectiveness of the proposed method is verified via simulation.
Keywords
Lyapunov methods; adaptive control; asymptotic stability; closed loop systems; discrete time systems; dynamic programming; linear systems; optimal control; uncertain systems; Bellman equation; adaptive dynamic programming technique; asymptotic stability; closed-loop system; dynamic quantizer; error bound quantization; infinite horizon optimal regulation problem; optimal adaptive controller scheme; policy iterations; quantization errors; standard Lyapunov stability; uncertain quantized linear discrete time system; unknown dynamics; Asymptotic stability; Equations; Mathematical model; Optimal control; Quantization; Stability analysis; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
Conference_Location
Maui, HI
ISSN
0743-1546
Print_ISBN
978-1-4673-2065-8
Electronic_ISBN
0743-1546
Type
conf
DOI
10.1109/CDC.2012.6425803
Filename
6425803
Link To Document