Design of adaptive T-S fuzzy-neural controller for a class of robot manipulators using projection update laws

Author

Chien, Yi-Hsing ; Lee, Tsu-Tian ; Wang, Wei-Yen

Author_Institution

Dept. of Electr. Eng., Nat. Taipei Univ. of Technol., Taipei, Taiwan

fYear

2010

fDate

10-13 Oct. 2010

Firstpage

1255

Lastpage

1260

Abstract

An on-line tracking controller design based on using T-S fuzzy-neural modeling for a class of general robot manipulators is investigated in this paper. Also, we use projection update laws to tune adjustable parameters for preventing parameters drift. In addition, stability of the closed-loop systems is proven by using strictly-positive-real (SPR) Lyapunov theory. The proposed overall scheme guarantees that all signals involved are bounded and the outputs of the closed-loop system asymptotically track the desired output trajectories. Finally, an example including two cases confirms the effectiveness of the proposed method.

Keywords

Lyapunov methods; adaptive control; closed loop systems; control system synthesis; fuzzy control; fuzzy neural nets; manipulators; neurocontrollers; stability; T-S fuzzy-neural modeling; adaptive T-S fuzzy-neural controller; closed-loop systems; on-line tracking controller design; projection update laws; robot manipulators; stability; strictly-positive-real Lyapunov theory; Artificial neural networks; Simulation; T-S fuzzy-neural model; projection update law; robot manipulator;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems Man and Cybernetics (SMC), 2010 IEEE International Conference on

Conference_Location

Istanbul

ISSN

1062-922X

Print_ISBN

978-1-4244-6586-6

Type

conf

DOI

10.1109/ICSMC.2010.5642419

Filename

5642419