A design method of optimal control system by use of neural network

Author

Nakanishi, Hiroaki ; Kohda, Takehisa ; Inoue, Koichi

Author_Institution

Dept. of Aeronaut. & Astronaut., Kyoto Univ., Japan

Volume

2

fYear

1997

fDate

9-12 Jun 1997

Firstpage

871

Abstract

This paper proposes a method to design an optimal control system by use of a neural network. Because the normal backpropagation (BP) method cannot be applied to this case, we choose Powell´s conjugate direction algorithm for training the neural network. In a regulator problem, the neural network functions as a state feedback controller, and in a servo problem it functions as both feedfoward and feedback controller. The proposed method can be applied to various problem where conventional methods cannot be applied. Simulation results show the effectivity of the proposed method

Keywords

closed loop systems; control system synthesis; discrete time systems; learning (artificial intelligence); multilayer perceptrons; neurocontrollers; optimal control; servomechanisms; state feedback; Powell´s conjugate direction algorithm; design method; feedfoward controller; neural network; optimal control system; servo problem; state feedback controller; Algorithm design and analysis; Design engineering; Design methodology; Multi-layer neural network; Neural networks; Optimal control; Performance analysis; Regulators; Servomechanisms; Stationary state;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks,1997., International Conference on

Conference_Location

Houston, TX

Print_ISBN

0-7803-4122-8

Type

conf

DOI

10.1109/ICNN.1997.616139

Filename

616139