Adaptive fuzzy-neural observer for a class of nonlinear systems

Author

Leu, Yih-Guang ; Lee, Tsu-Tian

Author_Institution

Dept. of Electron. Eng., Hwa-Hsia Coll. of Technol. & Commerce, Taipei, Taiwan

Volume

3

fYear

2000

fDate

2000

Firstpage

2130

Abstract

Based on the H_∞ control technique and the strictly positive real Lyapunov (SPR-Lyapunov) design approach, an adaptive fuzzy-neural observer tuned online for a class of uncertain (unknown) nonlinear systems is developed. Unlike the results of Marino et al. (1992, 1995), the assumption that the uncertain system nonlinearities only are restricted to the system output is not required. Moreover, the adaptive fuzzy-neural observer provides the modeling error (and the external bounded disturbance) attenuation with H_∞ performance, obtained by a Riccati-like equation. Finally, simulation results demonstrate that the proposed observer yields satisfactory performance

Keywords

H^∞ control; Lyapunov methods; adaptive control; fuzzy control; neurocontrollers; nonlinear systems; observers; uncertain systems; H_∞ control; adaptive control; bounded disturbance; fuzzy control; neurocontrol; nonlinear systems; observer; strictly positive real Lyapunov method; uncertain systems; Adaptive control; Adaptive systems; Attenuation; Control systems; Error correction; Nonlinear control systems; Nonlinear systems; Observers; Optimal control; Programmable control;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics and Automation, 2000. Proceedings. ICRA '00. IEEE International Conference on

Conference_Location

San Francisco, CA

ISSN

1050-4729

Print_ISBN

0-7803-5886-4

Type

conf

DOI

10.1109/ROBOT.2000.846344

Filename

846344