期刊
CONTROL ENGINEERING PRACTICE
卷 143, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.conengprac.2023.105787
关键词
Model predictive control (MPC); Dynamic matrix control (DMC); Three-term DMC; Performance and robustness; Coal-fired power plant
In this study, a three-term Dynamic Matrix Control (DMC) algorithm using quadratic programming is developed and compared with the traditional two-term DMC algorithm. Simulation studies and real-life tests show that the three-term DMC algorithm outperforms the two-term DMC algorithm in control effectiveness.
Most MPC (Model Predictive Control) algorithms used in industries and studied in the control academia use a two-term QP (quadratic programming), where the first term is the weighted norm of the output errors, and the second term is that of the input increments. In this work, a DMC (Dynamic Matrix Control) algorithm that uses three-term QP is developed and studied, where the third term is the weighted norm of the output increments. A relationship between the three-term DMC and the two-term DMC is established; and based on that, ideal closed-loop response curves are derived. These results are useful for the tuning of the three-term DMC. Then, a method for comparing two control methods is proposed and it is shown that the three-term DMC outperforms the two-term DMC. The findings are verified using simulation studies. Finally, the three-term DMC is successfully applied to a 1030 MW ultra-supercritical coal-fired power plant. According to simulation study using the identified model, in comparison to traditional two-term DMC, there is a roughly 10% reduction in the standard deviation of load tracking error for similar control efforts. In real-life tests on the power plant, the performance of the three-term DMC is compared to that of the existing PID controller. The load rate of change increased from 0.8%/min to 1.5%/min while the standard deviation of steam pressure decreased 38%; the standard deviations of the main steam temperature and reheat steam temperature decreased more than 40% with their mean values increased by more than 2 degrees C and 4 degrees C respectively.
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