The Design Of A Multi-Degree-of-Freedom Manipulator Fuzzy Adaptive Control System

With the advancement of science and technology and the development of modern industry,modern industrial production tasks and operating environments have become more complex,requiring robots to have higher intelligence and environmental adaptability in the automated production process in order to improve the controllability and accuracy of operations.In order to improve the trajectory tracking control performance of the system,an adaptive fuzzy PID controller is designed to improve the trajectory tracking control performance.The software and hardware platform of the six DOF Manipulator is built.The hardware platform is based on the control needs of the manipulator,and adopts ARM and FPGA integrated design method to provide multiple expansion interfaces.The whole system is modular design,including core control module,servo motor and communication module.The functions of each module are clearly divided and clear,and the standard communication mode is adopted among each other.The software platform is used to configure the manipulator control system by the upper computer control software.The controller designed in this paper is an adaptive fuzzy-PID controller based on the multi-objective clonal selection algorithm.The controller can suppress the internal and external disturbances by using the nonlinear PID feedback in the adaptive fuzzy PID controller.The controller can be used to suppress the internal and external disturbances.According to the tracking error and the change rate of tracking error,the appropriate proportions,integral and differential parameters are selected under different working conditions,and the control parameters of the manipulator are adjusted online according to the actual working conditions.In this paper,on the basis of building a soft and hard platform with six degrees of freedom,the MATLAB simulation software is used to build the control system of the manipulator by using the S function module in the Simulink,and the simulation is carried out.The simulation results show that the whole system has been well optimized compared with the traditional PID control system.It can effectively compensate the influence of uncertainty factors caused by the internal and external disturbances on the trajectory tracking control accuracy.The controller can make the system realize the fast and stable tracking control of the target trajectory.In the track tracking process,the trajectory tracking error is small,and the desired control requirements are achieved,and the controller is embodied.