Research On Control Strategy Of Lens Micro-displacement Moving Mechanism Based On Piezoelectric Drive

In digital microscopy,in order to acquire sequential images uniformly,the precise positioning between the lens and the loading platform needs to be realized through the relative step micro displacement motion.The micro-displacement moving mechanism based on piezoelectric driven lens has a series of advantages,such as compact structure,high resolution,fast response speed,strong anti-electromagnetic interference ability,etc.,which is very suitable for miniaturization and accurate positioning,and has a wide application prospect in the optical field.In this thesis,a micro-displacement motion mechanism based on piezoelectric drive is designed.The mechanism is composed of displacement amplifying mechanism,displacement output mechanism and auxiliary assembly mechanism.The displacement amplifying mechanism is composed of bridge mechanism and two secondary lever coupling mechanism,and three working modes are realized to meet the needs of various working conditions.The working principle analysis of each working mode,the selection of each parameter,the theoretical derivation of magnification,the influence of different quality lenses and the finite element simulation verification are carried out.In order to accurately describe the hysteresis nonlinear characteristics of the piezo-driven lens moving mechanism,the PI hysteresis modeling process of the lens moving mechanism was analyzed,and the parameter selection and identification methods were studied.Considering the defects of PI hysteresis model of lens moving mechanism,BP neural network and Play operator are combined to improve it.At the same time,the genetic algorithm is used to obtain the optimal solution between the initial weight and threshold value of the neural network,which overcomes the shortcomings of strong randomness and slow convergence rate of the neural network,and the genetic algorithm optimized back propagation neural network(GA-BP)based on PI to improve the hysteresis nonlinear model.Results Simulation results show that the relative error of the proposed improved model is reduced to 0.0467%,which can be accurately modeled and easily combined with the controller design.Based on the improved hysteresis nonlinear model,the inverse correlation model is established and the feedforward compensation is carried out.In view of the shortcomings of PID feedback controller,the integral element is improved,the differential link is passivated,and the whole controller is improved recursively.Fuzzy control is introduced to adjust the control parameters so that the control system has a certain adaptive ability.Genetic algorithm is used to optimize the initial value of fuzzy PID off-line to improve the control efficiency.A compound control system combining feedforward control and feedback control was established,and the simulation experiment of piezoelectric driven lens moving mechanism was carried out,and the effectiveness of the control system was verified.The results show that the improved control system of the piezoelectric driving lens moving mechanism has the advantages of rapid response and strong anti-interference ability.In order to verify the performance of the designed piezoelectric driving lens moving mechanism,the natural frequency test of the piezoelectric driving lens moving mechanism,the output force and output displacement performance test under each working mode and the piezoelectric hysteresis nonlinear compensation experiment were carried out.The results show that the first order natural frequency of the designed piezoelectric driving lens moving mechanism is 55.41 Hz.The maximum output displacement is 558.3μm and the maximum load is 49.33 N,which meets the current usage requirements.In addition,in order to verify the proposed improved control scheme,the trajectory tracking and dynamic response experiments under different expected displacements and different loads were carried out.The proposed improved control scheme showed that the control accuracy of trajectory tracking could reach 90%.In terms of dynamic response,the delay time was reduced to less than 2ms,the control response was completed within 60 ms,and the steady-state error was less than 0.09%.It has the advantages of fast response speed and small steady-state error.At the same time,it can dynamically adjust the control parameters and has strong anti-interference.