DocumentCode :
425552
Title :
Optimal control synthesis of a class of nonlinear systems using single network adaptive critics
Author :
Padhi, Radhakant ; Unnikrishnan, Nishant ; Balakrishnan, S.N.
Author_Institution :
Dept. of Mech. & Aerosp. Eng., Missouri Univ., Rolla, MO, USA
Volume :
2
fYear :
2004
fDate :
June 30 2004-July 2 2004
Firstpage :
1592
Abstract :
Adaptive critic (AC) neural network solutions to optimal control designs using dynamic programming has reduced the need of complex computations and storage requirements that typical dynamic programming requires. In this paper, a "single network adaptive critic" (SNAC) is presented. This approach is applicable to a class of nonlinear systems where the optimal control (stationary) equation is explicitly solvable for control in terms of state and costate variables. The SNAC architecture offers three potential advantages; a simpler architecture, significant savings of computational load and reduction in approximation errors. In order to demonstrate these benefits, a real-life micro-electro-mechanical-system (MEMS) problem has been solved. This demonstrates that the SNAC technique is applicable for complex engineering systems. Both AC and SNAC approaches are compared in terms of some metrics.
Keywords :
adaptive control; approximation theory; computational complexity; control system synthesis; dynamic programming; large-scale systems; micromechanical devices; neural net architecture; neurocontrollers; nonlinear control systems; optimal control; adaptive critic neural network; approximation error reduction; complex engineering systems; computational complexity; computational load; costate variables; dynamic programming; microelectromechanical system; nonlinear systems; optimal control equation; optimal control synthesis; single network adaptive critic architecture; state variables; stationary equation; storage requirements;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 2004. Proceedings of the 2004
Conference_Location :
Boston, MA, USA
ISSN :
0743-1619
Print_ISBN :
0-7803-8335-4
Type :
conf
Filename :
1386804
Link To Document :
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