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  • Gazi University Journal of Science
  • Volume:28 Issue:1
  • Trajectory Tracking Control of an Industrial Robot Manipulator Using Fuzzy SMC with RBFNN

Trajectory Tracking Control of an Industrial Robot Manipulator Using Fuzzy SMC with RBFNN

Authors : Ayça AK, Galip CANSEVER, Akın DELİBAŞI
Pages : 141-148
View : 26 | Download : 11
Publication Date : 2015-02-23
Article Type : Other Papers
Abstract :One of the main problems associated with Sliding Mode Control insert ignore into journalissuearticles values(SMC); is that a whole knowledge of the system dynamics and system parameters is required to compute the equivalent control. Neural networks are popular tools for computing the equivalent control. In fuzzy SMC with Radial Basis Function Neural Network insert ignore into journalissuearticles values(RBFNN);, a Lyapunov function is selected for the design of the SMC and RBFNN is proposed to compute the equivalent control. The weights of the RBFNN are adjusted according to an adaptive algorithm. Fuzzy logic is used to adjust the gain of the corrective control of the SMC. Proposed control method and a PID controller are implemented on an industrial robot manipulator insert ignore into journalissuearticles values(Manutec-r15);. Experimental results indicate that the proposed method is a good candidate for trajectory control applications of robot manipulators.
Keywords : Neural Network, Fuzzy Logic, Sliding Mode Control, Robot Control

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