Research On Forward Kinematics And Control Method Of 6-DOF Parallel Platform

The 6-DOF parallel platform has many advantages of large bearing capacity,good rigidity,high accuracy,fast dynamic response and without accumulativeerror,so it is widely used in many fields,such as robot,motion simulator,newtype machine and spacecraft docking.In this paper,the 6-DOF parallel platform isused as an equipment to simulate the ship moving in the sea,and it hascontrollable,non-destructive,economical and reliable abilities compared with theactual trial,so it has very broad application prospects.In order to improve theperformance of the 6-DOF parallel platform,this paper mainly focuses on forwardkinematics and control strategy.Firstly,this paper introduces the structure of 6-DOF parallel platform indetail,establishes the platform dynamics model with Lagrange method,analyzesthe mathematical model of hydraulic cylinders and servo valve,and establishesthe hydraulic servo model.So these establish the foundation for the realization of6-DOF parallel platform controller.Secondly,this paper uses the advantages of neural network method with nolimit of initial value and Newton-Raphson method with high accuracy,andpresents a forward kinematics method which is put the neural network methodand the Newton-Raphson method together.It uses the neural network method tosolve the imprecise solution of forward kinematics,and then uses theNewton-Raphson method to solve the precise solution after a few iterations withthe imprecise solution as initial iteration,so it has well complementary with thetwo methods.In order to improve the learning ability of neural network method,itpresents renewable proportion space contracting particle swarm optimizationalgorithm with non-complete evolution and space contracting,and analyzesparticle swarm optimization algorithm with contraction factor and contractioncycle in detail.It uses renewable proportion space contracting particle swarm optimization algorithm to optimize the weights of neural network to improveaccuracy of the forward kinematics.Thirdly,this paper presents a robust composite control structure withhydraulic servo systems of complex outside interference and system parametersperturbation,and it is composed of PD controller,robust inner loop controller,zero phase error tracking controller and dynamic fuzzy neural network controller.In this composite control structure,PD controller realizes feedback control toensure the stability of the whole system;robust inner loop controller can inhibitthe influence of uncertainty outside interference and system parametersperturbation;zero phase error tracking controller can improve the rapid response;dynamic fuzzy neural network controller realizes the compensation of PDcontroller to further improve the suppression of uncertainty outside interferenceand system parameters perturbation.Finally,in order to reduce the modeling error and the external disturbance ofthe 6-DOF parallel platform,it designs a robust tracking control strategy based oninverse dynamics compensation,which is used Lyapunov direct method to obtainthe robust control law with the skewed symmetry of (?)(q)-2C(q,(?)) indynamics model.The control strategy uses inverse dynamics to compensate theinner loop and designs the robust controller based on dissipation theory in outerloop,and it can guarantee the tracking errors uniformly and ultimately boundedand enhance the robustness of the system.Simulation results show that the forward kinematics and the control methodsof 6-DOF parallel platform are all effective.