Research On High Precision Flatness Fuzzy Neural Control For Wide Strip Steel Cold Mill

In this paper, author chooses flatness intelligent control for the prevalent high precise cold strip mill as research object, has deeply researched on theory, simulating and industry experiment, and has achieved new fruit.The key of flatness control is flatness pattern recognition. For the problems of the general methods, the method of fuzzy, and method of network for flatness recognition, author has in the first place put forward a fuzzy neural model for flatness recognition using Legendre multinomial as basic pattern, using fuzzy logic expert experience and using genetic-BP algorithm for optimizing, with only three input signals and 3 output signals. The model is simple, fast, precise, self-adapting steady and its nodes have clear physical meanings;so it meets the need of flatness control for cold strip mill, giving easily useful and new method for flatness recognition.Hydraulic bend is basic part of flatness control system. Whether it is dynamic and steady indicates the performance of flatness control system. For hydraulic bend flatness control system, Author has built electric and hydraulic servo pressure (hydraulic pressure) control system algorithm and put forward genetic single nerve cell self-adapting fuzzy control strategy which is used to raise product ratio, make full use of hydraulic force and improve the dynamic performance of mill system. Otherwise, author has explored the method of building bend flatness auto control model using non-parse theory, which overcomes a lot of difficulties in building system model.Flatness predicting model is important to design flatness control system and precise flatness predicting model is needed either in analyzing the control characteristic of the machines adjusted or in controlling on line. Fast and precise flatness predicting mode certainly will raise the control precision of flatness control system. Flatness predicting model is designed by conventional theory model analyzing three-dimensional plastic deformation in rolling metal and elastic deformation of roll. Precise math mode is designed hardly because it is restricted by nature of metal, rolling condition, and rolling equipment etc and flatness control system is many-variable, non-linear, high combined and time-delay;so theory model is hardly used in flatness predicting on line. In order tobuild a more fast and precise model of flatness prediction, author has built on-line fuzzy-neural predicting model based on product data. Elman dynamic recursive network and fuzzy control are introduced in the flatness predicting model and it overcomes a lot of defects, such as iterative operation, time-consuming operation, unable take into account on-line dynamic disturb, easily making dynamic model static model in many-lay ahead feedback network, exploring a new non-parse method of building flatness model and resolving many problems in building complex system model.Because flatness control is many-variable, non-linear, high combined and time-delay, it is difficult to control flatness by use of classical control based on experiential model or modern control. To solve the problem, author has put forward a new intelligent method of flatness control and has built self-adapting fuzzy single nerve cell double-model intelligent control model. According to the combine of fuzzy control and nerve cell control, they can complement each other and make full use of flatness control power. A fuzzy switch pattern is put forward to make the both control signals of the model switch steadily and produce the control signal of the double-model controller, realizing the combine of the advantage of the both control model and improving control performance obviously.Flatness control intelligent model is offered and stimulating software is compiled by combining flatness pattern recognizing model, hydraulic bend control model, flatness predicting model and flatness control model, building flatness control system of cold strip mill and altering the state of controlling flatness by experience.Choosing flatness fuzzy neural network control of high precise wide cold strip mill with theory and engineer practice meaning as research object, author has done a lot of theory, simulating and industry experiment research on flatness pattern recognition, hydraulic bend control, flatness predicting on line, and flatness close loop control. It is important to not only the improvement of flatness high precise control but also the technology of flatness control in theory and engineer application.