Study of Intelligent Controller Based on FWN Oriented to Indirect Nonmetal Rapid Tooling

Abstract

As one key technology of Rapid Tooling (RT), Indirect Nonmetal Rapid Tooling (INRT) has been used widely, so this paper analyzed the modeling process of INRT and concluded that the velocity of stirring and casting are key factors which affect products quality and production efficiency. In nature, just need to control the speeds of driving motors. In order to resolve problems of existing modeling equipments, such as strong dependency on operators experience and low control precision, this paper studied an intelligent controller model based on Fuzzy Wavelet Network (FWN) which integrated wavelet analysis and fuzzy neural network technologies. The structure and implementation algorithm of FWN are introduced in detail. After considering the advantages of Permanent Magnet Synchronous Motor (PMSM), the INRT equipments use it as driving motors. Because it is nonlinear, uncertain, coupled, sensitive and multivariable system, this paper made improvement on traditional IP controller, FWN acted as error compensator which can compensate for disturbance influence and trace expected speed in real time. The IP intelligent controller based on FWN can strengthen interference ability. The robustness of this control system has been verified by simulation experiment. This controller realized closed loop control of stirring and casting motor and improved the products quality and control precision of INRT.