Direct adaptive NN control of a class of nonlinear systems

Author

Ge, Shuzhi S. ; Wang, Cong

Author_Institution

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

Volume

13

Issue

1

fYear

2002

fDate

1/1/2002 12:00:00 AM

Firstpage

214

Lastpage

221

Abstract

In this paper, direct adaptive neural-network (NN) control is presented for a class of affine nonlinear systems in the strict-feedback form with unknown nonlinearities. By utilizing a special property of the affine term, the developed scheme,avoids the controller singularity problem completely. All the signals in the closed loop are guaranteed to be semiglobally uniformly ultimately bounded and the output of the system is proven to converge to a small neighborhood of the desired trajectory. The control performance of the closed-loop system is guaranteed by suitably choosing the design parameters. Simulation results are presented to show the effectiveness of the approach

Keywords

adaptive control; neurocontrollers; nonlinear control systems; closed-loop system; controller singularity; direct adaptive neural-network control; nonlinear systems; nonlinear uncertain systems; strict-feedback form; unknown nonlinearities; Adaptive control; Backstepping; Control nonlinearities; Control systems; Linear feedback control systems; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control; Stability;

fLanguage

English

Journal_Title

Neural Networks, IEEE Transactions on

Publisher

ieee

ISSN

1045-9227

Type

jour

DOI

10.1109/72.977306

Filename

977306