Title :
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
fDate :
27 Jun-2 Jul 1994
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;
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
DOI :
10.1109/ICNN.1994.374673
