DocumentCode
2457134
Title
Understand direct NDP with linear quadratic regulation
Author
Lei Yang ; Si, Jennie ; Tsakalis, K.S.
Author_Institution
Dept. of Electr. Eng., Arizona State Univ., Tempe, AZ, USA
fYear
2004
fDate
2-4 Sept. 2004
Firstpage
374
Lastpage
379
Abstract
This work falls into the general area of approximate dynamic programming. Direct NDP designs are further analyzed using classic control-theoretic sensitivity arguments. The relationship between direct NDP and LQR designs are discussed due to their resemblances in system performance functions. The cart-pole benchmark problem is used to demonstrate the possibility that direct NDP sometimes produces LQR-like designs. It is also shown that given a well-designed direct NDP control system, one can find a corresponding LQR design which exhibits comparable closed-loop performance. The convergence properties are studied by taking direct NDP under the linear LQR control environment.
Keywords
control system synthesis; convergence; dynamic programming; linear quadratic control; neurocontrollers; cart-pole benchmark problem; classic control-theoretic sensitivity arguments; linear quadratic regulation; neural dynamic programming; Approximation methods; Control systems; Convergence; Cost function; Design optimization; Dynamic programming; Equations; Regulators; State estimation; System performance;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control, 2004. Proceedings of the 2004 IEEE International Symposium on
ISSN
2158-9860
Print_ISBN
0-7803-8635-3
Type
conf
DOI
10.1109/ISIC.2004.1387712
Filename
1387712
Link To Document