Abstract

Multiple Degrees of Freedom (DOF) parallel robots possess the advantages of being compact structure, great stiffness, stability and high accuracy, so such platforms have been widely used in application areas as diverse as the spacecraft motion simulators, radio telescopes, and medical rehabilitation devices. In this paper, after giving a brief review on the control strategies for parallel robot, a 6-DOF robot system for medical purposes based on simulation as well as real environment is established. In order to improve the position tracking accuracy for such objects with time-varying and nonlinear parameters, a practical fuzzy adaptive controller is designed based on the kinematics of parallel platform, where fuzzy inference units are utilized to modify the PID parameters in real-time by using the position feedback from the robot actuators. Finally, both virtual and actual experiment results demonstrate that the proposed algorithm is able to effectively reduce the position tracking errors compared with the traditional PID controller, and the reliability and feasibility of such parallel robotic system can also be guaranteed.

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