Research On Adaptive Control Method Of Manipulator Based On Fuzzy Compensation

With the rapid development of science and technology in the world today,the application of robotics has become wider and wider.At present.manipulators have more and more applications in the areas of industrial production,cosmonautical survey and detection,deep-sea regional development,and military activity hazard investigation.Therefore,the algorithm research on the trajectory tracking control and path planning control of manipulators is of landmark significance.As the core of the manipulator system,the control research of manipulators has been highly valued by many scholars.The most important problem that needs to be solved at present is how to improve the trajectory control accuracy of the manipulator,thereby replacing humans with more complicated and more demanding tasks in terms of trajectory control accuracy.In the robot control process,its system has the characteristics of nonlinearity,uncertainty,variability and strong coupling.Especially during its movement,there will be some uncertain non-linear items,such as friction.In order to eliminate the effects of friction and achieve the purpose of' improving system control performance,many scholars have proposed some compensation methods.However,the friction model during the actual movement of manipulators is often complex and unknown.In this paper,using the approximation characteristics of fuzzy systems,an adaptive fuzzy compensation scheme for friction,interference,and other uncertainties is designed to counteract these uncertainties.The influence of the manipulator's movement process improves the tracking accuracy of the manipulator's trajectory.The main work of this paper is as follows:In the simulation process,the movements of the joints of the manipulators reflect the movement trajectory of the manipulators at the end of the manipulator.Therefore,the kinematics equations of the manipulators are established first.Then through the Lagrangian function,the dynamic model of the manipulator is deduced.Finally,the current types of f-riction models,such as the Coulomb model,Stribeck model,Karnopp model,and Dahl model,were investigated and analyzed for the types,properties and characteristics of the static and dynamic friction models,and the friction model closest to the actual situation was selected.Robot model.It lays the foundation for simulation verification of control solutions.For general servo systems and robot systems,PID control methods common in the industrial production range are used for trajectory tracking control in consideration of friction.According to the simulation results,the control effect was observed and the "flat top" and”dead zone" phenomena of the tracking curve were found.The reason is that the system friction is multi-valued and discontinuous when the system is in the zero-crossing and low-speed range,resulting in the control error changing.Big.It can be concluded that the design process of the PID control method is simpler than that of the PID control method,but it does not take into account the impact of friction and other uncertainties,and can not meet the performance requirements of stability.accuracy,speed,and anti-jamming at the same time,and has poor robustness.The control accuracy is low.For the shortcomings of PID control,a control method with fuzzy compensation is adopted,that is,from the approximation characteristics of the fuzzy system,an adaptive controller is designed to approach the uncertain items in the system based on the double joint robot model.Based on this,a robust term is added to reduce the approximation error in the control process.Comparing the results of simulation experiments with PID control results,it can be proved that when faced with the nonlinear uncertainties in the system,the adaptive control method based on fuzzy compensation can effectively eliminate the influences and improve the control precision of the manipulator.