DocumentCode :
2930781
Title :
Intelligent backstepping sliding-mode control using recurrent interval type 2 fuzzy neural networks for a ball-riding robot
Author :
Cheng-Kai Chan ; Ching-Chih Tsai
Author_Institution :
Dept. of Electr. Eng., Nat. Chung Hsing Univ., Taichung, Taiwan
fYear :
2012
fDate :
16-18 Nov. 2012
Firstpage :
169
Lastpage :
174
Abstract :
This paper presents an intelligent backstepping sliding-mode control using recurrent interval type 2 fuzzy neural networks (RIT2FNN) for motion control of a ball-riding robot. After brief description of the dynamic model of the robot with viscous and Coulomb frictions, a backstepping sliding-mode control using hierarchical aggregated sliding control method and RIT2FNN is proposed to accomplish robust trajectory tracking of the robot in the presence of mass variations, terrain-dependent viscous and Coulomb frictions. Computer simulations are conducted to illustrate the effectiveness of the proposed control method.
Keywords :
friction; fuzzy neural nets; mobile robots; motion control; neurocontrollers; position control; recurrent neural nets; robot dynamics; variable structure systems; Coulomb friction; RIT2FNN; ball-riding robot; hierarchical aggregated sliding control method; intelligent backstepping sliding-mode control; mass variation; motion control; recurrent interval type 2 fuzzy neural network; robot dynamic model; robot trajectory tracking; viscous friction; Backstepping; Equations; Mathematical model; Mobile robots; Sliding mode control; Vectors; backstepping; ball-riding robot; recurrent interval type 2 fuzzy neural networks (RIT2FNN); sliding-mode control; trajectory tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Theory and it's Applications (iFUZZY), 2012 International Conference on
Conference_Location :
Taichung
Print_ISBN :
978-1-4673-2057-3
Type :
conf
DOI :
10.1109/iFUZZY.2012.6409695
Filename :
6409695
Link To Document :
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