Research On Identification And Control Of Robotic Arms With Uncertainty And External Disturbance

Manipulator system has the advantages of replacing people to complete all kinds of complex,precise and dangerous work and improving labor productivity.It is widely used in all kinds of industrial places.The uncertainty and external disturbance in the manipulator system will affect the position tracking accuracy of the manipulator.How to overcome the uncertainty and external disturbance in the system has important research value and significance for improving the position tracking accuracy of the manipulator.In this thesis,for the manipulator system with uncertainty and external disturbance,a control method to solve the problem of uncertainty and external disturbance is designed based on parameter identification,sliding mode control,neural network control,uncertainty and disturbance estimator,active disturbance rejection control and other methods.The main research contents are as follows:(1)The dynamic model of the manipulator is established according to the Lagrange method,and the reasons for the uncertainty and external disturbance of the system are analyzed.A dynamic feedforward controller based on identified parameters is designed.Multiple neural networks are used for adaptive dynamic parameters online identification.The identified parameter information is introduced into the feedforward channel to realize dynamic feedforward control.The robust term is set to make up for the weak antidisturbance ability of feedforward control.The simulation results show that the dynamic feedforward controller based on on-line parameter identification achieves good control effect.(2)Considering that with the increase of the degree of freedom of the manipulator,the problem of insufficient calculation force of the controller will appear in the method of parameter identification using multiple neural networks,a controller combining neural network and sliding mode robust term is designed.Firstly,a single neural network is used to approximate the overall uncertainty.Then,aiming at the system stability problem caused by the approximation error and external disturbance of the neural network,a sliding mode robust term based on the new reaching law is designed to compensate to ensure the system stability.Finally,the simulation is carried out under different external disturbance conditions.The simulation results show that the designed controller can effectively improve the position tracking accuracy and has good anti-disturbance ability.(3)Because there are many parameters of neural network and the adjustment of parameters is relatively complex,in order to simplify the calculation,a sliding mode controller based on uncertainty and disturbance estimator is designed.Firstly,the sliding mode controller for position tracking is designed.Then,the uncertainty and disturbance estimator is designed to estimate and compensate the uncertainty and disturbance.Finally,the simulation is carried out under different external disturbances.The simulation results show that the method is effective in dealing with parameter uncertainty and external disturbances,realizes no overshoot control,and the uncertainty and disturbance estimator can effectively suppress the chattering of sliding mode control.(4)In order to reduce the dependence on model information,an active disturbance rejection controller combining linear extended state observer and sliding mode controller is designed.Firstly,the system is decoupled and rewritten into the form of extended state equation,and the coupling part uncertainty and external disturbance,that is,the total disturbance,are acted as a new system state.Then,the extended state observer is used to estimate and compensate the total disturbance.Finally,a nonlinear feedback controller based on terminal sliding mode is designed to realize fast position tracking.The simulation results show that the designed controller can effectively deal with the uncertainty and external disturbance of the manipulator system,improve the response speed and reduce the sliding mode chattering.