Robotic arm dynamics modelling and robust control based on model recognition method

This paper analyzes the dynamics modelling and robust control of the robotic arm by using a model-based defines method. Firstly, the motion coupling relationship between the front and rear joints of the robotic arm is analyzed, and two kinds of motion decoupling modules based on planetary gear and pulley system are proposed, and the decoupling principle of the motion decoupling module is analyzed to realize the mechanical decoupling of the joint motion of the robotic arm. After that, a comprehensive test bench of two-degree-of-freedom robotic arm joint motion is constructed, and the factors influencing the decoupling effect of the mechanical decoupling module are analyzed through experiments to verify the effectiveness of the motion decoupling module. At the same time, the analysis also shows that: with the increase of the number of robotic arm joints, the number and volume of required decoupling modules increase, and the application of decoupling modules will significantly increase the volume, weight, and torque loss of the robotic arm, thus leading to the robotic arm’s large load to weight ratio which is not an advantage, therefore, mechanical decoupling is not suitable for robotic arms with more than 3 degrees of freedom. The design of a fuzzy incremental controller based on the model dialectic method is proposed for application in parallel robot control; it has universal approximation characteristics and can self-organize the velocity and position information of the parallel robot legs, and dynamically adjust the output of the controller by the designed affiliation function and control rules.