Specialized Affine Approximation for Nonlinear Systems Output Tracking Using Neural Networks

Authors:
Tsurng-Jehng Shen;Chorng-Shyr Jou;Meng-Jey Youh;Chia-Tang Chen
Affiliations:
Hsing Wu College, Taipei County, Taiwan, China 244;Hsing Wu College, Taipei County, Taiwan, China 244;Hsing Wu College, Taipei County, Taiwan, China 244;Hsing Wu College, Taipei County, Taiwan, China 244
Venue:
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Year:
2009

Citing 3
Cited 0

Multilayer feedforward networks are universal approximators

Neural Networks
Nonlinear control systems: an introduction (2nd ed.)

Nonlinear control systems: an introduction (2nd ed.)
Adaptive control of nonlinear multivariable systems using neural networks

Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

A special model of artificial neural networks has been developed for the purpose of output tracking of a class of nonlinear systems and an original training structure basing on the error back-propagation algorithm is introduced. This approach which, on the ground of input-output observations, turns feasible the use of inverse control techniques appears much simpler than other existing neural control approaches for inverse control problem. Simulation results reveal that the proposed approach presents rapid training and good tracking performances.