Direct Adaptive NN Control of Nonlinear Systems in Strict-Feedback Form Using Dynamic Surface Control

Author

Zhang, Tianping ; Ge, Shuzhi Sam

Author_Institution

Yangzhou Univ., Yangzhou

fYear

2007

fDate

1-3 Oct. 2007

Firstpage

315

Lastpage

320

Abstract

In this paper, direct adaptive neural control is investigated for a class of strict-feedback nonlinear systems with both unknown system functions and virtual control gain functions. The explosion of complexity in traditional backstepping design is avoided by utilizing dynamic surface control (DSC) and introducing integral-type Lyapunov function. It is proved that the proposed design method is able to guarantee semi-global uniform ultimate boundedness of all signals in the closed-loop system, with arbitrary small tracking error by appropriately choosing design constants.

Keywords

Lyapunov methods; adaptive control; closed loop systems; control system synthesis; feedback; neurocontrollers; nonlinear control systems; nonlinear dynamical systems; closed-loop system; direct adaptive neural net control; dynamic surface control; integral-type Lyapunov function; strict-feedback nonlinear system; virtual control gain function; Adaptive control; Backstepping; Control systems; Explosions; Lyapunov method; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Programmable control;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control, 2007. ISIC 2007. IEEE 22nd International Symposium on

Conference_Location

Singapore

ISSN

2158-9860

Print_ISBN

978-1-4244-0440-7

Electronic_ISBN

2158-9860

Type

conf

DOI

10.1109/ISIC.2007.4450904

Filename

4450904