Long Stroke Precision Stage Control System Based On ARM

Nowadays, with the develop of equipment manufacturing industry and large scale integrated circuits and other high-tech, ultra-precision positioning stage is higher required, long-displacement and high-resolution precision stage system have very important position in sophisticated industrial processing and scientific research fields. In precision processing fields, long-displacement and high-resolution both are incompatible. The purpose of this paper is design a Macro-micro Actuators precision stage, which use of segmented design, combined with stepper motors and piezoelectric ceramics, compose Macro-micro Actuators, and the control platform is based on ARM embedded system.Precision workstation has dual-stage, the macro-stage uses stepper motor and precision lead screw for feed, drive micro-stage for high-speed positioning, ensure the response speed of whole system. Micro-stage uses piezoelectric ceramics, which advantage include high-resolution, small size and good stability. But there are also creep, hysteresis and other nonlinear shortcomings. So this paper is divided into three parts to design.First, the embedded operating system design. In this paper, the embedded system is WinCE6.0, because of it's kernel compilation process basically are modular, easy to develop and can be used in implement control systems. The main task is to make the kernel, and complete the bottom-level driver. Finally, compile and download into the control system, then test the system performance in experiment, it works stable.Second, the macro-stage design. This component is totally the hardware design, using subdivision control chip of stepper motor, built the external circuit around subdivision control chip, achieve the stepper motor control. In experiment, the stepper motor is working stable, and obtaining good accuracy.Third, the micro-stage design. Micro-stage is mainly composed of piezoelectric ceramics, but it has non-linear hysteresis phenomenon, control system can not directly control it. So need the piezoelectric ceramics modeling. In this part , the main research on nonlinear hysteresis phenomena modeling, the method uses to the PI model with RBF neural network. Finally proved by Matlab simulation, this model has a good property to fit the nonlinear hysteretic material, and having good predictive ability.