Dynamic Parameter Identification And Control System Design Of 6-DOF Industrial Robot

Industrial robot system is a complex multi-input multi-output nonlinear system with time-varying,strong coupling and nonlinear dynamics characteristics.Trajectory tracking control is an important aspect of industrial robot control.Trajectory tracking control requires each joint of the robot to track the continuous and time-varying desired trajectory.The desired trajectory is often complex,with impact on the velocity,acceleration and even acceleration.Due to the high complexity of the robot system and the continuous time-variability of the tracked track,the trajectory tracking control of the robot is very difficult and the control accuracy is difficult to guarantee.In this paper,the kinematics and dynamics modeling,dynamic parameter identification,and adaptive controller design of the robot are studied in order to improve the trajectory tracking accuracy and dynamics of the robot system.Firstly,the hardware and software of the whole experimental research platform for dynamic parameter identification and adaptive control based on dynamic model are introduced.Then,according to MDH method,the kinematics parameters necessary for analyzing the dynamics of the six-degree-of-freedom industrial robot were obtained,the dynamic model was constructed by Newton-Euler iteration method,and the dynamic expression was derived by symbol calculation software SYMORO+.Then the linearized model of the robot and the set of minimum inertia parameters are analyzed,and a set of minimum inertia parameters of the six-degree-of-freedom industrial robot is deduced.The finite term Fourier series is studied as the excitation trajectory of the dynamic parameter identification experiment.Combined with Hadamard's inequality,the optimization objective function of the excitation trajectory parameters is proposed,and the MATLAB fmincon function is used to calculate the excitation trajectory parameters.Studied on least square parameter identification method.Introduced to central difference algorithm which is uesd to calculate the joint angular velocity and angular acceleration and RLOESS filtering method.Then,the model adaptive PD control method is studied,the adaptive control system is designed,and the stability of thecontrol system is proved.Finally,the minimum inertia parameters are identified through the excitation trajectory tracking experiment.Through the experiments of tracking the excitation trajectories and the verifying trajectories,the parameter identification method is validated by analyzing the root mean square error between the measured moment and the estimated moment based on the identification model.The feasibility of the adaptive PD control system is verified by the expected trajectory tracking experiment.