Research On Control Optimization Algorithm For Robot Arm Trajectory Tracking

Manufacturing technology has become more sophisticated background in the modern industrialization,work performance manipulator for industrial robot arm put forward higher requirements,especially in the manufacturing section involve sophisticated devices,which requires the actuator at the end of the arm to achieve complete tracking of the desired trajectory.The manipulator system is a nonlinear system that is difficult to accurately establish mathematical models,uncertain parameters,and strong coupling.In the actual operation process,it faces the interference of complex factors,and there will be sudden changes in the end load,and the system parameters cannot be adjusted in time.At present,considering the possible variation range of system control input and parameter adaptive adjustment during system operation are the hot topics of modern industrial robot arm research.At the same time,it is an important part of the system design process to design a trajectory optimal controller for the minimum energy consumed in a complete working cycle of the mechanical arm in the industrial manufacturing process.The main research contents of this paper are as follows.Firstly,the mathematical model of the manipulator is established to solve the kinematic equations.The kinematic equations and the physical properties of the joints are combined to derive the dynamic equations for the system analysis.The adaptive iterative learning control method is used to improve the error of the system trajectory tracking,optimize the research results obtained,design the controller with initial learning and adopt the exponential variable gain control method to improve the response speed of the system and improve the machinery.The tracking accuracy of the arm system enables complete tracking of the desired trajectory.Secondly,considering the physical characteristics of the manipulator and the change of the end load,a possible condition of limited control input is proposed.Then the fuzzy adaptive inversion control method can make the mechanical arm system still have good tracking effect.The simulation results also prove that the possible situation has little effect on the stability of the system and the trajectory tracking effect.Finally,according to the minimum energy requirement of the mechanical armsystem in the actual working environment,the optimal trajectory obtained by trajectory planning is used as the expected input of the double joint manipulator trajectory tracking control system.In the trajectory planning process,the crossover and mutation factor adaptive strategy is used to improve the differential evolution algorithm,which can improve the flexibility of the algorithm.The simulation proves that the optimization algorithm can make the system jump out of the local optimum and effectively improve the trajectory tracking accuracy of the system.