Title :
Adaptive RBFNN Based Fuzzy Sliding Mode Control for Two Link Robot Manipulator
Author :
Liu, Fei ; Fan, Shaosheng
Author_Institution :
Dept. of Electr. & Inf. Eng., Changsha Univ. of Sci. & Technol., Changsha, China
Abstract :
A adaptive Radial basis function neural network (RBFNN) based fuzzy sliding mode control scheme for two link robot manipulator is proposed in this paper. In the scheme, RBFNN is used to approximate system dynamic, the weights of the RBFNN are changed according to adaptive algorithm to ensure the system state hitting the sliding surface and sliding along it. In order to guarantee the stability and the convergence of the system, the sliding mode control gain is adjusted by the adaptive fuzzy systems to compensate the network approximation error and the external disturbances. The simulation results demonstrate that the control scheme is effective.
Keywords :
adaptive systems; approximation theory; fuzzy control; manipulators; radial basis function networks; variable structure systems; adaptive RBFNN; adaptive algorithm; adaptive fuzzy systems; adaptive radial basis function neural network; approximate system dynamic; fuzzy sliding mode control; network approximation error; sliding mode control gain; sliding surface; system state hitting; two link robot manipulator; Adaptive algorithm; Adaptive control; Fuzzy control; Fuzzy neural networks; Manipulator dynamics; Programmable control; Radial basis function networks; Robots; Sliding mode control; Stability; adaptive fuzzy gain control; radial basis function neural network (RBFNN); sliding mode control; two link robotic manipulator;
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
DOI :
10.1109/AICI.2009.276
