| With the development of China’s industrial modernization process，the cold-rolledstrip products have become an integral part of our national economy. At present, the focusof China’s cold-rolled strip production is transferring in accordance with the requirementsof high-tech, high-precision, low-cost and low-pollution. How to further enhance thequality and accuracy of the production of cold-rolled strip, it is the question that needs themajority of the practitioners in steel industry and technical researchers to further study.The thickness control system of cold rolling mill export is a time delay system.Because the signal that the thickness of the export of cold rolling mill can not betransferred to control unit timely, it causes a great deal of difficulty in AGC system. If thetime-delay problem of export thickness monitoring can be solved, it can improve thequality of cold-rolled strip material and reduce the rejection rate, which has importantpractical significance.The mathematical model of the cold mill rolling thickness control system has beenestablished on the basis of referring to the relevant literature in this paper. Aimed at thetime lag problem in the thickness closed-loop control system, Smith predictor was viewedas a breakthrough to solve the problem and the research and discussion to the questionwere launched. In the case of a known mathematical model, to improve the controller partof Smith predictor, an improved scheme was proposed which combined the fuzzy PIDcontroller with Smith predictor. In the actual rolling process, many uncertainties areexisted in the system, so accurate mathematical model is obtained difficultly. A new Smithpredictor control scheme based on neural network identification was given to overcomethe dependence that Smith predictor to the mathematical model. As the simulation resultsshowed, the response characteristics, robustness and the application of the Smith predictorall could be improved in both two schemes. |
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