Research On Trajectory Tracking Control Of 3-DOF Parallel Manipulator

With the development of global economy and science and technology,it has important scientific research and practical engineering significance to realize the high-precision control of the mechanical arm and meet the needs of diversified process precision.3-DOF parallel manipulator is a kind of nonlinear and strongly coupled parallel mechanism system,the parallel mechanical structure makes the mathematical model more complicated and the control more difficult.This paper focuses on the friction compensation,dead zone estimation and end task space control of a 3-DOF parallel manipulator,the corresponding control strategy is proposed to realize the tracking control of the parallel manipulator.The main research contents of the thesis are as follows:Firstly,the dynamic analysis of the 3-DOF parallel manipulator is performed to simplify the structural model of the parallel manipulator,the Euler-Lagrangian equation is used to establish the dynamic model of the parallel manipulator,it lays the foundation for subsequent controller design.Secondly,the friction term compensation problem exists for the tracking control of the parallel manipulator.Design an adaptive fuzzy sliding mode controller,the adaptive fuzzy system estimates the dynamic friction term in real time and improves the branch tracking accuracy of the parallel manipulator,compensate for dynamic friction terms in the parallel manipulator model.The Lyapunov analysis method is used to prove the stability of the closed-loop system,the tracking control of each branch of the parallel manipulator is realized.Thirdly,based on the trajectory tracking control problem of the parallel manipulator in the case of the branch torque output dead zone.An adaptive neural network integral sliding mode control algorithm is proposed,the integral type switching function is introduced to reduce the steady-state error caused by external disturbances.Dead zone nonlinear compensation for actuators such as ball screws and pulleys in parallel manipulators,design an adaptive neural network compensator,the adaptive RBF neural network is used to approximate the unknown term on the line,and the dead zone compensation of each branch torque output of the parallel manipulator is realized.By designing the Lyapunov function,the convergence of the closed-loop system is analyzed,the simulation results show that the designed controller has the ability to compensate for dead zone nonlinearity.Finally,a fractional-order terminal sliding mode controller is designed for the trajectory tracking control problem of the end of the parallel manipulator in the task space.For the chattering phenomenon existing in the terminal sliding mode controller,a fractional operator with a time decay characteristic is introduced into the switching function,the chattering of the parallel manipulator is weakened by the fractional sliding mode,it also ensures that the state of the parallel manipulator converges to the equilibrium point of the system for a limited time.The simulation data shows that the trajectory tracking control of the end of the parallel manipulator in the task space is realized.