Modeling And Control Of Piezoelectric Macro-micro Platforms

The piezoelectric macro and micro precision positioning platform is widely used in national defense and military industry,precision machining,MEMS manufacturing,optical precision instrument measurement and so on.With the rapid development of precision machining technology,the requirements for the stroke and accuracy of the positioning system are getting higher and higher.However,the traditional single-drive positioning technology is difficult to realize such technical problems as large stroke and high precision.The macro-micro combined with two-stage driving technology is superior to single-drive positioning technology in stroke,response speed and positioning accuracy.Researchers at home and abroad have done a lot of research about the macro and micro two-level drive platform,and made suggestions for high-precision manufacturing technology,which is of great significance to the development of modern science and technology.In this paper,DC servo motors and piezoelectric actuators are used as the power components of the macro and micro drive platforms,and a one-dimensional motion platform with large stroke and high precision is built.DC servo motor is used as displacement device with large stroke,and piezoelectric actuator is used to compensate displacement error to realize precise positioning.The main contents of this article are summarized as follows:(1)An explicit hysteresis model for piezoelectric actuators and the corresponding inverse compensation method are proposed.In order to reduce the impact of the hysteresis on the system,the method of constructing inverse compensation is usually used to solve it.Since the implicit input in the system will cause the difficulty of constructing the inverse,an explicit hysteresis model is proposed and described by a differential equation.To ensure that the designed controller is stable,it is proved that the nonlinear auxiliary variables of the model are bounded,and the effectiveness of the model is proved by parameter identification through the improved PSO algorithm.Finally,the inverse multiplication structure(IMS)is used to construct directly inverse compensation to verify the superiority of the explicit hysteresis model.(2)A neural network adaptive controller for piezoelectric ceramic actuators is designed.In this controller,in addition to the input of the system itself,the lag input is also used as a part of the neural network input,and then the hysteresis compensation is carried out by using the unknown function in the neural network approximation error dynamics.In order to ensure the boundedness of the closed-loop system,starting from the Lyapunov stability theorem,the update law and control law of the controller are derived.Connect the designed controller with the piezoelectric actuator,and observe the tracking effect by given a complex signal.Finally,it is proved that the design of the controller is effective.(3)The macro and micro positioning platform system is designed,and the DC servo motor and the piezoelectric actuator are respectively controlled by the RBF neural network sliding mode controller and the neural network adaptive controller,so that the piezoelectric macro and micro platform can track the set route quickly and accurately.Finally,simulation experiments are used to verify that the accuracy and stroke of the macro-micro positioning platform system meet the specified requirements.