Variable structure control for 6-6 parallel manipulators based on cascaded CMAC

This paper proposes a novel control scheme with focus on the-uncertainty of the complex robot system, which combine cascaded Cerebellar Model Articulation Controller (CMAC) with Variable Structure Control (VSC). Firstly, a improved CMAC is used to learn the uncertainty of robot system, and it is used as a feed-forward compensator, fast tracking error convergence and better learning stability is obtained through use cascaded CMAC. Then, a VSC term is used to reduce the effect of CMAC estimate error and unrepeatable disturbances. The control law is chose based on Lyapunov direct method. Simulation of 6-6 parallel manipulator trajectory tracking show the good stability and accuracy are obtained.