Trajectory Tracking Control Of Mutli-DOF Robotic Manipulators

In this thesis,the trajectory tracking control strategy is studied for multi-DOF robotic manipulator system with high nonlinearity,strong coupling and parameter uncertainty.Firstly,the mathematical model of the Denso VP6242 manipulator is analyzed.The forward kinematics model of the manipulator is established by the standard D-H method,and the inverse kinematics model of the manipulator is established by alge-braic method.The joint angle solved by the inverse kinematics model is substituted into the forward kinematic model,the simulation data shows that the accuracy of in-verse kinematic model can achieve 10^-16.The dynamic model of the robotic manipu-lator is established according to the Lagrange equation,which provides control object for simulation verification of subsequent control methods.a neural network terminal sliding mode control method based on time delay es-timation is proposed for the trajectory tracking control of multi-DOF robotic manipu-lator.Different from traditional sliding mode control,the proposed control method is not constrained by model information.By using the time delay estimation,the model information and external disturbance are estimated,and the dynamic model of manip-ulator is simplified to a local model.Then the terminal sliding mode controller is de-signed by the non-singular terminal sliding mode surface and the improved fast power approaching law,which can make the system converge to the equilibrium point in a finite time.An adaptive neural network and a network approximation error adaptive term are designed to compensate the delay estimation error,which improves the con-trol accuracy and anti-jamming ability.The simulation and experimental data show that the proposed control method can effectively improve the control performance of the manipulator control system,enhance the robustness to the disturbance,and reduce the system chattering.Finally,the thesis proves that the fast power approaching law is a second-order sliding mode essentially,but it can't exert the second-order sliding mode characteris-tic when the system has uncertainty.In order to make the fast power approaching law exert the second-order sliding mode characteristic in the multi-DOF robotic manipu-lator system,a second-order terminal sliding mode control method based on sliding mode disturbance observer is proposed.Based on the simplified local model in Chap-ter 3,the sliding mode controller is designed by using non-singular terminal sliding mode surface and fast power approaching law,and a new sliding mode disturbance observer is designed to compensate delay estimation error in a finite time.The Lya-punov function method proves that the proposed method can make the sliding mode variable and its derivative of the system converge to zero in a finite time,which means the proposed method is a second-order sliding mode method.Due to the use of the sliding mode disturbance observer,the proposed method shows stronger robust-ness than other second-order sliding mode methods.Simulation and experimental re-sults show that the proposed method can effectively improve the convergence speed and tracking accuracy of the manipulator and enhance the robustness to disturbance.