期刊
JOURNAL OF PROCESS CONTROL
卷 54, 期 -, 页码 81-89出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jprocont.2017.03.006
关键词
System modeling; Karhunen-Loeve decomposition; Least squares support vector machines; Distributed parameter system; Rademacher complexity
资金
- GRF project from RGC of Hong Kong [CityU: 11205615]
- National Natural Science Foundations of China [51475096, U1501248]
In this paper, a dual least squares support vector machines (LS-SVM) is proposed to model the thermal process. The infinite-dimensional system is first transformed into a finite-dimensional system through space-time separation. Then, the dual LS-SVM model is to approximate the two nonlinearities embedded in the system. Through space-time synthesis, the dual LS-SVM based spatiotemporal model is able to approximate the complex DPS with inherent coupled nonlinearities. The generalization performance of the proposed model is discussed using Rademacher complexity. Finally, simulations on a curing process demonstrate the effectiveness of the proposed modeling method. (C) 2017 Elsevier Ltd. All rights reserved.
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