Research on Closed-loop Control Method for Arm Position Under Mechanical Drive of Robot Joints
Due to the nonlinear dynamic effects involved in the arm movement of robots,the motion mode of the arm is complex,and the closed-loop control of the arm position is difficult and has low accuracy.Therefore,a closed-loop control method for arm position under mechanically driven of robot joints is proposed.Torque sensors are utilized to expand torque feedback on the joints to complete the dynamic modeling of mechanically driven robots.The dynamic parameters are estimated through the dynamic model.Based on improvement to the PID controller using fuzzy neural network,the fuzzy neural network can serve as the feedforward part of the PID controller,resulting in more accurate control signals provided by the input dynamic parameters.Taking the expected trajectory parameters,joint torque parameters,and other dynamic parameters as the control objectives of the PID controller,the particle swarm optimization algorithm is used to continuously iterate to find the optimal solution,to achieve closed-loop control of the robot arm position.The experimental results show that the method has strong control stability,high control accuracy,with a joint angle error within 1％,and small joint torque variation.
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