Direct adaptive control for a class of MIMO nonlinear systems using neural networks

Author

Ge, S.S. ; Li, G.Y. ; Zhang, J. ; Lee, T.H.

Author_Institution

Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore

Volume

49

Issue

11

fYear

2004

Firstpage

2001

Lastpage

2006

Abstract

In this note, direct adaptive neural network (NN) control is studied for a class of multiple-input-multiple-output nonlinear systems based on input-output discrete-time model with unknown interconnections between subsystems. By finding an orthogonal matrix to tune the NN weights, the closed-loop system is proven to be semiglobally uniformly ultimately bounded. The control performance of the closed-loop system is guaranteed by suitably choosing the design parameters.

Keywords

MIMO systems; adaptive control; closed loop systems; discrete time systems; matrix algebra; neurocontrollers; nonlinear control systems; MIMO systems; closed-loop system; direct adaptive control; discrete-time system; multiple-input multiple-output systems; neural networks; nonlinear systems; orthogonal matrix; Adaptive control; Automatic control; Control systems; Lyapunov method; MIMO; Neural networks; Nonlinear control systems; Nonlinear systems; Robustness; Uncertainty; 211;multiple-output; 65; Adaptive control; MIMO; NNs; discrete-time systems; multiple-input&#; neural networks; systems;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/TAC.2004.837561

Filename

1356120