| The development of modern coiler system is mainly aiming at improving the yield and quality of product. Hydraulic servo system used in coiler is mainly to realize the step-by-step control. By using the servo system, vibration and striking are largely decreased, the accidents are reduced, and the level of automation is largely improved, as well as the quality of production.This paper is focused on step-by-step control system for coiler of hot rolling mill, and based on the real work process of coiler at worksite, a mechanical model for coiler control system is built at laboratory used for research work. This is the first time in China to develop an electro-hydraulic servo system for this step-by-step control system.In the thesis, neural network adaptive control method in the coiler control system is studied in detail. Artificial neural network (ANN), which is a rapidly developing crossing subjects, has many advantages such as parallel storing, parallel processing of information, teaching itself etc. Genetic algorithm (GA), a probability search algorithm, simulates the mechanism of natural choose and natural genetic and its main features are group research strategy and individual information exchange which do not depend on gradient information. ANN and GA have a broad application in intellectual control. This thesis realizes the real-time control of hydraulic servo system by using neural network adaptive control method, which is used the features and virtues of ANN and GA.This thesis establishes a GA-NNI model for identification of hydraulic system. Utilizing Windows98 as its O.S., the control software is developed by using Visual C++ language. The results show that the software has strong application value and its interface is interactive and easy to operate.Experiments show that in the system, step-by-step control is realized, the utilization rate of materials is gained. This model lays the basis for developing the better coiler.
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