Support vector machine-based multi-model predictive control |
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Authors: | Zhejing BAO Youxian SUN |
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Affiliation: | 1. College of Electrical Engineering,Zhejiang University,Hangzhou Zhejiang 310027,China 2. State Key Laboratory of Industrial Control Technology,Zhejiang University,Hangzhou Zhejiang 310027.China |
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Abstract: | In this paper,a support vector machine-based multi-model predictive control is proposed,in which SVM classification combines well with SVM regression.At first,each working environment is modeled by SVM regression and the support vector machine network-based model predictive control(SVMN-MPC)algorithm corresponding to each environment is developed,and then a multi-class SVM model is established to recognize multiple operating conditions.As for control,the current environment is identified by the multi-class SVM model and then the corresponding SVMN.MPCcontroller is activated at each sampling instant.The proposed modeling,switching and controller design is demonstrated in simulation results. |
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Keywords: | Multi-model predictive control Support vector machine network Multi-class support vector machine Multi-model switching |
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