A neural approach for control of nonlinear systems with feedback linearization

Author

He, Shouling ; Relf, K. ; Unbehauen, Rolf

Author_Institution

Lehrstuhl fur Allgemeine und Theor. Elektrotech., Erlangen-Nurnberg Univ., Germany

Volume

9

Issue

6

fYear

1998

fDate

11/1/1998 12:00:00 AM

Firstpage

1409

Lastpage

1421

Abstract

Several schemes for feedback linearization using neural networks have been investigated and compared. Then an approach to design a neurocontroller in the sense of feedback linearization is introduced. The contents include: (1) full input-output linearization when a system has relative degree n; (2) partial input-output linearization when a system has relative degree r (r<n); and (3) approximate linearization when the involutivity condition does not hold. Corresponding programs and examples are given to illustrate the proposed methodology

Keywords

control system synthesis; feedback; linearisation techniques; multilayer perceptrons; neurocontrollers; nonlinear control systems; approximate linearization; feedback linearization; full input-output linearization; neural approach; nonlinear systems; partial input-output linearization; Control systems; Helium; Linear approximation; Linear feedback control systems; Multi-layer neural network; Neural networks; Neurocontrollers; Neurofeedback; Nonlinear control systems; Nonlinear systems;

fLanguage

English

Journal_Title

Neural Networks, IEEE Transactions on

Publisher

ieee

ISSN

1045-9227

Type

jour

DOI

10.1109/72.728391

Filename

728391