Research On Trajectory Tracking Adaptive Control Algorithm For Industrial Manipulators

With the advancement of intelligent manufacturing and industrial manufacturing upgrades,industrial manipulators have been applied widely.Some high-speed?high-precision industrial situations demand on the higher performance of controller and positioning accuracy of the industrial manipulators.In a complex industrial application environment,the performance of the industrial manipulators always be affected by the nonlinear factors of joint flexible components,joint coupling,friction,and disturbance of the load.It's difficult to get the accurate model of the system;What's more,the control system of manipulators is a multi-input with multi-output,strong coupling,and time-varying nonlinear parameters,it's hard to guarantee the accuracy of the system for trajectory tracking.In this thesis,the research object is the industrial manipulators.The adaptive control algorithm on the industrial manipulators control system is studied,for the purpose of improving the accuracy of tracking and dynamic performance of the manipulators.Firstly,according to the principle of energy,the dynamic model of the multi-links manipulator is deduced through the Euler-Lagrangian method,and the manipulators is described as a whole system.The dynamic characteristics of the manipulators system has been researched.The inertial parameters are linear with the system.The existence of non-linear factors such as Coriolis force and centrifugal force in the manipulator's model,the manipulator cannot ensure high accuracy while tracking the time-varying trajectory with linear and steady-state parameter controllers.The Euler-Lagrangian method was used to perform dynamic mathematical modeling of the planar two-joint manipulators,and the manipulators' model was linearly transformed to inertial parameters.Secondly,designing the controller for the industrial robotic system,this thesis analyzes the reason why the robot's trajectory tracking accuracy is not high with the PD controller.The paper proposes adding another feedforward compensation controller which was based on the dynamic model of the robotic manipulators,in the control loop of the industrial robotic system.Adaptive controller and numerical simulation of the closed-loop control system of the industrial robotic system.What's more,taking into account the limitations that the parameters of controller are unmodifiable of the existing robotic control system.Considering the architecture of inner/outer control system,a new control system is proposed for the case while the torque loop is not open for users,and the outer loop is adaptive controller which is based on the dynamic model of the manipulators.The disturbance of nonlinear factors can be compensated proportionately.Simulation results show that the addition of an adaptive controller can improve the accuracy of the manipulators system for trajectory tracking.Generally speaking,the platform on computer always be designed for sending the instructions to controller the robotic manipulators.In this thesis,a platform on computer based on the existing robotic manipulators system has been designed so that users can design another outer controller algorithm for the manipulators.When the torque loop is not open to the users,the users still can utilize the platform to search the dynamical dynamic control algorithm by designing the outer controller.The results of simulation certify that the adding of outer controller can improve the accuracy of the industrial robotic system for trajectory tracking with high dynamic performance.Finally,the adaptive compensation algorithm based on the dynamic model of the manipulator proposed in this thesis is verified experimentally on the developed platform,and the algorithm is added to the front of existing controller of the industrial robotic system to track the time-varying trajectory.From the results of experiment,the conclusion is that the addition of the outer loop adaptive controller can improve the accuracy of the robot control system for tracking,and illustrate the effectiveness and rationality of the adaptive control algorithm proposed in this paper.