DocumentCode :
1515821
Title :
Neural dynamic optimization for control systems.II. Theory
Author :
Seong, Chang-Yun ; Widrow, Bernard
Author_Institution :
Dept. of Electr. Eng., Stanford Univ., CA, USA
Volume :
31
Issue :
4
fYear :
2001
fDate :
8/1/2001 12:00:00 AM
Firstpage :
490
Lastpage :
501
Abstract :
The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper mainly describes the theory of NDO, while the two other companion papers of this topic explain the background for the development of NDO and demonstrate the method with several applications including control of autonomous vehicles and of a robot arm, respectively
Keywords :
MIMO systems; computational complexity; dynamic programming; feedback; neural nets; optimal control; optimisation; autonomous vehicles; complexities; control systems; neural dynamic optimization; neural networks; nonlinear multi-input-multi-output systems; optimal feedback control; robot arm; Computer networks; Control systems; Dynamic programming; Feedback control; MIMO; Neural networks; Neurofeedback; Optimal control; Optimization methods; Vehicle dynamics;
fLanguage :
English
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
1083-4419
Type :
jour
DOI :
10.1109/3477.938255
Filename :
938255
Link To Document :
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