Deep Deterministic Policy Gradient and Active Disturbance Rejection Controller based coordinated control for gearshift manipulator of driving robot

In order to improve the shift precision of the gearshift manipulator, a coordinated control method for the gearshift manipulator based on the Deep Deterministic Policy Gradient (DDPG) and Active Disturbance Rejection Controller (ADRC) is proposed. Firstly, the kinematic model and dynamics model of the gearshift manipulator are established. Secondly, a coordinated control strategy is proposed to solve the target rotation angle of the servo motor, so as to deal with the nonlinear trajectory problem caused by the mechanical decoupling strategy. Then, an ADRC-based controller and a DDPG-based parameter adjuster are proposed. A DDPG model is established to adaptively adjust the control parameters of ADRC through the target rotation angle, actual rotation angle and rotation angle error. Finally, the theoretical stability proof and experimental verification of the proposed method are conducted. The test results show that the mean absolute error of the proposed method is 34% and 18% lower than that of ADRC and fuzzy PID methods. It shows the effectiveness of the method.