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