Fan Shaosheng
Changsha University of Science and Technology Changsha, 410004, Hunan, China
Wei Xing
Changsha University of Science and Technology Changsha, 410004, Hunan, China
Wang Xuhong
Changsha University of Science and Technology Changsha, 410004, Hunan, China
ABSTRACT
Adaptive Radial basis function neural network (RBFNN) based fuzzy sliding mode controller for underwater two joints manipulator in condenser is proposed. The RBFNN is used to approximate the manipulator system dynamics, the weights of the RBFNN are changed according to adaptive algorithm to hit the sliding surface and slide along it. In order to guarantee the stability and the convergence of the system, the sliding mode control gain is adjusted by adaptive fuzzy system to compensate the network approximation error and the external disturbances. The simulation results demonstrate that the proposed control scheme is feasible and effective.
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How to cite this article
Fan Shaosheng, Wei Xing and Wang Xuhong, 2013. Adaptive RBFNN based Fuzzy Sliding Mode Control for Underwater Two Joints
Manipulator in Condenser. Information Technology Journal, 12: 4755-4759.
DOI: 10.3923/itj.2013.4755.4759
URL: https://scialert.net/abstract/?doi=itj.2013.4755.4759
DOI: 10.3923/itj.2013.4755.4759
URL: https://scialert.net/abstract/?doi=itj.2013.4755.4759
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