NDLI: The multi-model predictive control method research on the outlet temperature control of ethylene cracking furnace

Content Provider	IEEE Xplore Digital Library
Author	Pang Qiang Tang Li-Xin Yuan Ming-Zhe Wang Xian-Peng
Copyright Year	2012
Description	Author affiliation: The Logistics Institute, Liaoning Key Laboratory of Manufacturing System and Logistics, Northeastern University, Shenyang 110819, China (Pang Qiang; Tang Li-Xin; Wang Xian-Peng) \|\| Department of industrial informatics, Shenyang Institute of Automation Chinese Academy of Sciences, Shenyang 110016, China (Yuan Ming-Zhe)
Abstract	Multi-model predictive control has become an effective method for handling the process of nonlinear system. But the traditional multi-model has large model tracking error and slow convergence speed when it is used to the MIMO nonlinear system solving the condition with large scale transition of operating condition. To solve these problems, a new structure of multi-model called multi-hierarchical model has been presented. This structure consists of many layers that each layer is comprised multiple models. The number of sub-models in each layer is different. In the condition of the same global operation space, upper layer has smaller number of sub-models, and lower layer has lager number of sub-models. Because of this structure, the models chosen from different layers can deal with the operating condition changed with large scale. But, the model switching method presented by the author is not flexible enough. In this paper, a new model switching method between different layers is presented. This method uses the error of output and the variation of output error as the layer switching rules. In the end of this paper, the simulation results of pH neutralization process which is a MIMO nonlinear system demonstrate that the multi-hierarchical model using the new model switching method is superior to single-hierarchical model with smaller model tracking error, better convergence speed and stability.
Starting Page	4044
Ending Page	4049
File Size	504269
Page Count	6
File Format	PDF
ISBN	9781467325813
ISSN	21612927
e-ISBN	9789881563811
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Chinese Assoc of Automati
Subject Keyword	nonlinear systems Coil outlet temperature Control Furnaces Multi-model Predictive Controllers Switches MIMO Temperature control Ethylene Cracking Furnace Nonlinear systems Fuzzy Clustering Method Predictive control
Content Type	Text
Resource Type	Article

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