A multi-objective fusion internal preload optimization method of redundantly actuated parallel robots for backlash prevention

In this paper, a multi-objective internal preload optimization method for a 4RRR redundantly actuated parallel robot is proposed. First, the dynamic model of a redundantly actuated parallel robot with redundancy of 2 is studied. The inverse dynamics model of the redundantly actuated parallel robot has an infinite set of control torque solutions that can track the desired trajectory, which makes the redundantly actuated parallel manipulators have the ability to complete additional tasks during operation. Taking the elimination of transmission clearance as an additional control task, the multi-objective internal preload optimization method is proposed, which takes the driving power, the switching loss of the drivers and the control force as the optimization goals. By utilizing this method, the backlash or clearance in the system can be eliminated, the power loss of the drivers can be reduced, and the operation precision can be improved. Some numerical simulations demonstrate the feasibility of the proposed method, and the robot shows stable motion characteristics.