Modeling of a linear motor´s stage based on genetic algorithm´s identification

The main objective of this paper is to improve the tracking accuracy of a linear motor´s stage. A DC brushless linear motor is used to actuate a gantry stage to perform printing process. To compensate the tracking error of the gantry stage due to nonlinear friction, the dynamics of the nonlinear static friction is formulated by the Hsieh-Pan model. Besides, genetic algorithm (GA) is studied to identify the optimal parameters of the plastic and nonlinear spring module. In addition, the proposed disturbance-observer based variable structure controller is used to improve the tracking response. To search the optimal parameters of the proposed controller, the system parameters´ identification is obtained using GA. To check the consistency, the proposed controller is implemented by the dSPACE DSP and the improved positional accuracy has been readily achieved within 0.1 micro meter.