Design of Automatic Control System for Mechanical Manufacturing Based on Improved Genetic Algorithm

With the rapid growth of social sci & tech, the related technologies of machinery manufacturing industry are constantly upgrading, which brings new opportunities as well as challenges to machinery manufacturing enterprises. As a product of high-tech field, there are often many factors that affect the stability of electrical automation control system in the actual mechanical manufacturing process. In this paper, mechanical automation technology and its application in mechanical manufacturing are studied, and an automatic control strategy of mechanical manufacturing based on improved GA is proposed. The simulation results show that the errors of the proposed automatic control algorithm for mechanical manufacturing are small, and the accuracy rate is high, reaching 96.31%. It can be seen from the error and precision of different algorithms that the performance of the automatic control algorithm for mechanical manufacturing in this paper is relatively good. Because it has the characteristics of little dependence on the problem and can obtain the global optimal solution, it can be applied to the optimization process of fuzzy controller, and can effectively determine the better control rules and membership functions, which provides extremely favorable conditions for the establishment of fuzzy control system.