Title :
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
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;
Conference_Titel :
Robotics and Automation, 2000. Proceedings. ICRA '00. IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-5886-4
DOI :
10.1109/ROBOT.2000.846344