Neural dynamic optimization for control systems.III. Applications

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

502

Lastpage

513

Abstract

For pt.II. see ibid., p. 490-501. 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 demonstrates NDO with several applications including control of autonomous vehicles and of a robot-arm, while the two other companion papers of this topic describes the background for the development of NDO and present the theory of the method, respectively

Keywords

MIMO systems; computational complexity; dynamic programming; feedback; neural nets; optimal control; autonomous vehicles; dynamic programming; neural dynamic optimization; neural networks; 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

10.1109/3477.938256

Filename

938256