Velocity-observer-based compensator for motion control of a reconfigurable manipulator

Parameter uncertainty and noise disturbance are unavoidable in the reconfigurable manipulator systems. To deal with this problem, we propose a velocity-observer-based neurofuzzy compensating control scheme. The update laws on weight, center and width-reciprocal of the membership function in the radial-basis-function-based (RBF) neurofuzzy are given by Lyapunov theorem. The proposed algorithm is proved to be ultimately uniformly bounded (UUB). The controller for a RRP (revolute-revolute-prismatic) reconfigurable manipulator is simulated and discussed. Simulation results show that the proposed algorithm is effective and satisfactory in tracking performance. Finally, simulation comparison between the velocity-observer-based RBF and the proposed neurofuzzy compensator is conducted and analyzed. Advantages and disadvantages for them are given.