DocumentCode
1515815
Title
Neural dynamic optimization for control systems. I. Background
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
482
Lastpage
489
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 background and motivations for the development of NDO, while the two other subsequent papers of this topic present the theory 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; dynamic programming; neural dynamic optimization; nonlinear multi-input-multi-output systems; optimal feedback control; optimal feedback solution; 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
10.1109/3477.938254
Filename
938254
Link To Document