Adaptive self-organizing neural network method for tracking problems of nonlinear dynamic systems

Author

Zheng-zhi, Wang ; De-wen, Hu ; Qi-ying, Xiao

Author_Institution

Dept. of Autom. Control, Nat. Univ. of Defence Technol., Hunan, China

Volume

5

fYear

1994

fDate

27 Jun-2 Jul 1994

Firstpage

2793

Abstract

In this paper a self-organizing neural network method of Kohonen (1990) and Matinez, Ritter, and Schulten (1989) is extended to solve the adaptive control problems of nonlinear dynamic systems. In each small region (receptive field), the nonlinear system can be expressed in linear vision approximately and controlled by neurons. The gaze points, receptive fields and control functions of neurons are regulated in self-organizing, learning and adaptive way. Several simulation examples verify the correctness and utility of this method

Keywords

adaptive control; neurocontrollers; nonlinear dynamical systems; self-adjusting systems; self-organising feature maps; adaptive control; adaptive self-organizing neural network method; gaze points; linear vision; nonlinear dynamic systems; receptive fields; tracking problems; Adaptive control; Adaptive systems; Control systems; Linear approximation; Neural networks; Neurons; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Programmable control;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-1901-X

Type

conf

DOI

10.1109/ICNN.1994.374673

Filename

374673