Industrial robot arm dynamic modeling simulation and variable-gain iterative learning control strategy design

Aiming at the difficulty of dynamic modeling of a hybrid robotic arm, a dynamic model system of industrial robotic arm based on Simscape Multibody was established with the MG400 robotic arm as the research object, which combines the motion control and data acquisition modules. The model is dynamically visualized and provides a convenient platform for studying the control algorithm of the robot arm. In response to the issues of sluggish speed and substantial position error in robot trajectory tracking control of a traditional controller, a variable gain iterative learning control methodology was designed. The robot arm control system model was employed to corroborate the trajectory tracking control under the stipulated target trajectory. The empirical outcomes indicate that in comparison to the traditional controller and the fixed-gain iterative learning controller, the variable-gain iterative learning controller can regulate the robot end trajectory more precisely, with swift tracking speed and accurate tracking posture, demonstrating commendable feasibility and portability. It offers an open-source research and development platform for the dynamic modeling of robot arm and a potent solution for the control strategy of robot arm.