Study On Performance And Control Of A 2-DOF Precision Positioning Stage Driven By Voice Coil Motors

With the continual development of technology,the requirements in the field of precision machining are more and more strict,especially for the requirement of machining accuracy.The precision machining accuracy depends largely on the performance and the accuracy of the micro positioning stage.Therefore,the research of micro positioning platform has a crucial impact on the improvement of precision machining and manufacturing performance.A 2-DOF planar flexure-based micro positioning stage driven by the voice coil motor was studied.The bearing capacity,static characteristics and dynamic characteristics were analyzed.The system identification and control scheme was studied.The static and dynamic performances of the system were analyzed by means of FEM simulation and experiment,and the bearing capacity and characteristics were investigated.When the system identification of the micro positioning stage was studied,the BP neural networks model was applied to identify the model owing to its strong ability to approach the nonlinear system.In order to overcome the shortcomings of the identification of the networks such as easily falling into local optimal solution and slower convergence speed,the genetic algorithm was utilized to optimize the BP neural networks.After the inverse model of the system was identified by network model,the neural network and PID compound(NN-PID)inverse control was applied to control the system.Then the simulations based on MATLAB / Simulink and the experimental testing based on the dSPACE controller were carried out which can prove the feasibility and the advantage of the way of identification and control methods based on e neural networks optimized by genetic algorithm.