DocumentCode
2751550
Title
Nonlinear system control via feedback linearization using neural networks
Author
Abdel, H.A. ; Sakr, Ahmed F. ; Bahgat, Ahmed
Author_Institution
Dept. of Electr. Power & Machines, Cairo Univ., Giza, Egypt
Volume
4
fYear
1996
fDate
3-6 Jun 1996
Firstpage
2238
Abstract
This paper addresses the problem of feedback linearization of nonlinear systems. The existing linearization methods require complete knowledge of the system model. A new method for feedback linearization, avoiding this requirement which is rarely satisfied in practice, is proposed. The method is based on artificial neural networks (ANNs) that emulate the plant´s Lie derivatives. Simulation results show satisfactory performance when the proposed ANN-based feedback linearization is included in a tracking control system
Keywords
Lie algebras; feedback; linearisation techniques; neural nets; neurocontrollers; nonlinear systems; tracking; Lie derivatives; SISO systems; feedback linearization; neural networks; nonlinear system control; tracking control; Artificial neural networks; Centralized control; Control systems; Least squares approximation; Linear approximation; Linear feedback control systems; Neural networks; Neurofeedback; Nonlinear control systems; Nonlinear systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1996., IEEE International Conference on
Conference_Location
Washington, DC
Print_ISBN
0-7803-3210-5
Type
conf
DOI
10.1109/ICNN.1996.549249
Filename
549249
Link To Document