The traditional robot visual servo control technology requires accurate dynamics and kinematics models of known ro-bots and the calibration of camera.However,due to the errors in the robot modeling and camera calibration,it is difficult to accu-rately build the error model,which affects the positioning accuracy and convergence speed of the robot vision servo system.To solve this problem,this paper proposes a robot vision servo technology based on Model-free Adaptive Control(MFAC).Using the input and output data of the system,this paper realizes adaptive visual servo control.Namely by the Jacobian matrix in the MFAC online estimation robot servo controller and combining with sliding mode controller,this paper achieves the precise track-ing task to targets.The results of simulation experiments show that the proposed method can ensure the smooth convergence of the servo controller under the unknown disturbance caused by the change of system parameters and reduce the system positioning error.
visual servomodel-free adaptive controlsliding mode control
万方数据
维普
