| Continuous industry plays an important role in national economy, and control method about it is also a focus question for researchers at home and abroad. Factually, we can regard the production of a continuous produce process in a stable state as maintaining the system run in repeat and steady.By using simple algorithm form and precise tracking results, iterative learning control has attracted extensive concern. Based on the repetition of the continuous industrial production combines with the idea of iterative learning control, continuous industrial process is divided into controlling periods of equal length in this dissertation. Then the iterative axis, which is needed in iterative learning control, has been specifically constructed. Iterative learning control can give a way to the modeling and time-delay problem when it is used in the process of continuous industrial production. Meanwhile, the feasibility and effectiveness of the algorithm has been verified by theoretical derivation and simulation. To sum up, the main contributions of this dissertation are summarized as follow:(1) The article analyzes characteristics of continuous industrial production process as well as the duplicated information in it.(2) The idea of cycle division for continuous industrial process is proposed, which is used to construct the basic form required by iterative learning control. Then considering the delay in the continuous industrial process, we choose the cycle of iterative learning control as the delay of system.(3) The convergence of iterative learning control for continuous industrial process is theoretically proved by constructing, analyzing and deducing. Further, experimental results illustrate its effectiveness.(4) The method of iterative learning control for continuous industrial process is applied to real production process on the basis of analyzing the firing process and its control circuit, thereby demonstrating the feasibility and utility of our proposed method. |
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