Adaptive Inverse Control In The Linear Motor Control System

With the rapid development of the electronics industry, increasing the scope of application of the chip, chip processing technology is more and more attention, it reflects a country the size of the IC manufacturing industry and the level of technology. Multi-line cutting is cutting large-diameter silicon rods are very effective one of the ways, but generally feed servo motor rotating ball screws, the subject of linear motor can be used to eliminate motor rotation by the rotation of the linear motion Mechanical transmission chain, with more dynamic response and excellent properties, is a current trend.Modern digital servo control system requirements to the high-precision, high-speed direction, in order to meet the needs of production, which must improve the accuracy of servo control system. In this paper, single-axis table in a straight line on the HS system, servo feed control issues more in-depth study on the basis of an improved BP neural network algorithm, hierarchical learning rate of entropy and means to enhance the function of the algorithm Learning efficiency and precision, combined with adaptive inverse control method, the design of permanent magnet synchronous linear servo motor neural network of adaptive inverse control system, gives the NNC and the detailed structure of the NNI.The traditional control method is based on mathematical models of the motor on the basis of the system's performance is often controlled by the model of precision and electrical parameters of impact, and regulators must be followed with a compromise between noise. This issue by using adaptive inverse control avoid as a result of the feedback that may be caused by the instability, at the same time ensure the system Dynamic control of the object and disturbance control could be dealt separately. Combined approach to the complex nonlinear function of neural networks, to avoid a mathematical model of the system, factors such as changes in the parameters of motor adverse effects, but also adaptive adjustment parameters, flexibility, with academic theories and practical significance Value. After simulation model put forward by the reasonableness of the increased table in response to the characteristics of a good dynamic and steady performance.