The industrial process control has the following characteristics: many constrained parameters, non-linear, big time-delay, model uncertainty and so on. Because of the above reasons, the precise mathematical model of the controlled object is hard to obtain. Even if we get the precise model, the optimization control according to ideal model is hard to maintenance its control effect. Therefore the actual demand of the advanced control appears. Among the application of advanced control in industrial process control field, the predictive control is relatively successful. The academic research and actual software development of predictive control in foreign countries have obtained great success and actual economic benefit. However the gap between the self-developed software of predictive control in our country and the foreign mature software product is very large. Developing our software of predictive control by ourselves has strong meaning to increase the control quality, to reduce the gap and to respond the country policy of energy-saving and ejection-decreasing. The focus of this thesis is on the research and software development of the dynamic matrix control. The thesis mainly describes the following two items: i. The theory research of the dynamic matrix control is relatively mature, therefore we put the focus on the software development. This software is developed in C# language based on the .net environment. The software is described in the international standard language - UML, including the use case diagram, class diagram, sequence diagram, state diagram and activity diagram etc. Through these diagrams, the software can be easily understood and developed by other researchers. ii. The essence of the DMC is the numerical optimization. In the actual project, the object usually has constrained multi-parameters and model uncertainty. The genetic algorithm can get fine optimization result and get rid of restrict of precise model, therefore satisfies the requirement of the software implementation and theory research of DMC. This thesis applies the genetic algorithm in the constrained multi-parameter dynamic matrix control, and states the brief implement steps. The optimization of the genetic algorithm needs a small period of time, so this kind of application is mainly used in the upper level control. The software took the improvement of the control algorithm and the addition of new algorithm into consideration in the design phase. We have developed the constrained single parameter DMC software, and tested in the company’s lab.
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