Research on Model Switching Method of Multi-hierarchical Model Predictive Control System
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摘要: 针对多层次多模型(Multi-hierarchical multi-model, MHM)预测控制系统的模型切换问题, 在分析各通道非线性程度对模型层次切换以及层次 间模型切换过程对系统动态特性的影响的基础上, 提出了一种新的模型切换方法. 并将此方法应用到多输入多输出pH 中和过程, 仿真结果表明, 该方法有效地改善了系统工况大范围跳变时的动态性能.Abstract: Based on analysis of the influence of different channels with different degrees of nonlinearity on the layer switching, and model switching between the layers on the dynamic performances, a model switching method is proposed. The simulation results of a pH neutralization process demonstrate that the multi-hierarchical model predictive control using the new model switching method can improve the dynamic performances with large setpoint change.
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[1] Chow C M, Kuznestov A G, Clarke D W. Successive one-step-ahead predictions in multiple model predictive control. International Journal of Systems Science, 1998, 29(9): 971-979[2] zkan L, Kothare M V, Georgakis C. Control of a solution copolymerization reactor using multi-model predictive control. Chemical Engineering Science, 2003, 58(7): 1207-1221[3] MacQueen J. Some methods for classification and analysis of multivariate observations. In: Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability. California: University of California Press, 1967. 281-297[4] Dunn J C. A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters. Journal of Cybernetics, 1973, 3(3): 32-57[5] Zhang T, Ramakrishnan R, Livny M. BIRCH: an efficient data clustering method for very large databases. In: Proceedings of the 1996 ACM SIGMOD International Conference on Management of data. New York, USA: ACM, 1996. 103-114[6] Dempster A P, Laird N M, Rubin D B. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, 1997, 39(1): 1-38[7] Norquay S L, Palazoglu A, Romagnoli J A. Nonlinear model predictive control of pH neutralization using Wiener models. In: Proceedings of the 13th IFAC World Congress. San Fransisco, USA: IFAC, 1996. 31-36[8] Mahmoodi S, Poshtana J, Jahed-Motlagh M R, Montazeri A. Nonlinear model predictive control of a pH neutralization process based on Wiener-Laguerre model. Chemical Engineering Journal, 2009, 146(3): 328-337[9] Qin S J. Recursive PLS algorithms for adaptive data modeling. Computers Chemical Engineering, 1998, 22(4-5): 503-514[10] Du J J, Song C Y, Li P. Multilinear model control of Hammerstein-like systems based on an included angel dividing method and the MLD-MPC strategy. Industrial and Engineering Chemical Research, 2009, 48(8): 3934-3943[11] Novak J, Bobal V. Predictive control of the heat exchanger using local model network. In: Proceedings of the 17th Mediterranean Conference on Control Automation. Thessaloniki, Greece: IEEE, 2009. 657-662[12] Chen Q H, Gao L J, Dougal R A, Quan S H. Multiple model predictive control for a hybrid proton exchange membrane fuel cell system. Journal of Power Sources, 2009, 191(2): 473-482[13] Dougherty D, Cooper D. A practical multiple model adaptive strategy for single-loop MPC. Control Engineering Practice, 2003, 11(2): 141-159[14] Kordon A, Fuentes Y O, Ogunnaike B A, Dhurjati P S. An intelligent parallel control system structure for plants with multiple operating regimes. Computers Chemical Engineering, 1997, 21(Supplement): S119-S124[15] Rodriguez J A, Romagnoli J A, Goodwin G C. Supervisory multiple regime control. Journal of Process Control, 2003, 13(2): 177-191[16] Du J J, Song C Y, Li P. A gap metric based nonlinearity measure for chemical processes. In: Proceedings of the 2009 American Control Conference. St. Louis, Missouri, USA: IEEE, 2009. 4440-4445[17] Liu L L, Zhou L F. Multi-hierarchical model predictive control based on K-means clustering algorithms. Advanced Materials Research, 2011, 211-212: 147-151[18] Zhou Lu-Wen, Zhou Li-Fang. Multiple modeling method based on advanced K-means clustering. Journals of University of Science and Technology, 2005, 35(Supplement): 62-67(周芦文, 周立芳. 基于改进K-means聚类算法的多模型建模方法. 中国科学技术大学学报, 2005, 35(增刊): 62-67)[19] Bordons C, Camacho E F. A generalized predictive controller for a wide class of industrial processes. IEEE Transactions on Control Systems Technology, 1998, 6(3): 372-387[20] Nie J H, Loh A P, Hang C C. Modeling pH neutralization processes using fuzzy-neural approaches. Fuzzy Sets and Systems, 1996, 78(1): 5-22
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