Affiliation:
1. School of Mechanical Engineering, Dalian University of Technology, Dalian, China
Abstract
This paper deals with the suppression of robotic joint buffetings for enhanced precision of trajectory tracking by means of fuzzy-based super-twist sliding mode control, which is illustrated with a fast pick-and-place parallel robot for material handling. Prior to control design, the joint motions and torques are measure to identify the dynamic parameters of the robot with recursive least square method, which is experimentally validated for the further model-based control design. In order to suppress the joint buffetings and to improve the tracking accuracy, the control law by integrating fuzzy algorithm and second-order sliding mode control is designed, where the control performance is evaluated by observing the joint dynamics, compared to the classical computed torque control and fuzzy sliding mode variable structure control. The experimental results and comparative study show the effectiveness of the developed control scheme, regarding the joint buffetings suppression and trajectory tracking precision. The main contribution lies in the integrated fuzzy algorithm and second-order sliding mode control for the model-based control design, with acceptable computational cost and trajectory tracking accuracy, from the perspective of actual engineering application.