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LS-SVM model based nonlinear predictive control for MCFC system

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Abstract

This paper describes a nonlinear model predictive controller for regulating a molten carbonate fuel cell (MCFC). In order to improve MCFC’s generating performance, prolong its life and guarantee safety, it must be controlled efficiently. First, the output voltage of an MCFC stack is identified by a least squares support vector machine (LS-SVM) method with radial basis function (RBF) kernel so as to implement nonlinear predictive control. And then, the optimal control sequences are obtained by applying genetic algorithm (GA). The model and controller have been realized in the MATLAB environment. Simulation results indicated that the proposed controller exhibits satisfying control effect.

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Authors and Affiliations

  1. Institute of Fuel Cell, Department of Automation, Shanghai Jiao Tong University, Shanghai, 200030, China

    Chen Yue-hua, Cao Guang-yi & Zhu Xin-jian

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  1. Chen Yue-hua
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  2. Cao Guang-yi
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  3. Zhu Xin-jian
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Additional information

Project (No. 2003 AA517020) supported by the Hi-Tech Research and Development Program (863) of China

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Chen, Yh., Cao, Gy. & Zhu, Xj. LS-SVM model based nonlinear predictive control for MCFC system. J. Zhejiang Univ. - Sci. A 8, 748–754 (2007). https://doi.org/10.1631/jzus.2007.A0748

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  • DOI: https://doi.org/10.1631/jzus.2007.A0748

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