Motion Control And Experimental Study Of Two Degrees Of Freedom Manipulator

Industrial robots are widely used in modern manufacturing industries,especially in the automated production line,which has become an essential tool.As the task becomes more and more complicated,the velocity response,motion stability,and the error of the end trajectory of robot are become more and more stringent.The traditional control algorithm can no longer meet the robot's control requirements.With the development of artificial intelligence,intelligent control algorithms are widely used in the motion control of robots because of the ir advantages,such as reliable control,good control effect,high computational efficiency,and ability to handle complex problems.This paper takes a two-degree-of-freedom manipulator as the research object,and controls the motion of the manipulator,which is based on PID and fuzzy PID.On the basis of the improved membership function of genetic algorithm for fuzzy controller is proposed.Build a test platform,The main research contents and research results are as follows :(1)In this paper,a kinematic model of a two-degree-of-freedom robotic arm is established,and Based on the Lagrangian method to establish its dynamic model,and calculate the coefficient matrix of the kinetic equation by the two-degree-of-freedom for the model manipulator,which is designed by experiment.(2)Analyze the control principle of PID and fuzzy PID algorithm,The advantages and disadvantages of the two-degree-of-freedom manipulator motion control are compared.In the absence of gravity and external disturbance s,to Simulate the PID and Fuzzy PID Algorithm,which Based on MATLAB Software for Controlling two-Degree-of-Freedom Manipulator.and to analyze and compare the response speed and overshoot of the two,the time required to achieve stability,and the fuzzy PID parameter setting time.The domain range of membership functions for fuzzy controllers mainly depends on experience,This task is based on the improved genetic algorithm to optimize the fuzzy controller membership function interval.Aiming that the disadvantages of slow convergence rate and poor global search ability for traditional genetic algorithms,using dynamic crossover method Orthogonal test to select excellent individuals for improvement,which based on MATLAB software,to simulate and analyse the two-degree-of-freedom robotic arm.By comparing with the analysis result of fuzzy PID algorithm and traditional genetic algorithm for fuzzy PID optimization algorithm,It is verified that the improved genetic algorithm has a better effect in the motion control of the two-degree-of-freedom manipulator.(3)A test control platform is built,and study the principle of Ether CAT communication and the basic functions of the host software Twin CAT.In addition,the servo drive parameters are Configured,and analyze the running stability of the motor through the monitoring software ASDA_Soft.Hybrid Programming Based on Twin CAT PLC and VC++ Programming Based on Twin CAT PLC and VC++,to implement the PID and Fuzzy PID for Motion Control of Two Degrees of Freedom Manipulator.Through experiments,the rationality of the studied algorithm is verified.