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ZJUS-A
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2007, Vol. 8 Issue (5): 748-754    DOI: 10.1631/jzus.2007.A0748
Environmental and Energy Engineering     
LS-SVM model based nonlinear predictive control for MCFC system
CHEN Yue-hua, CAO Guang-yi, ZHU Xin-jian
Institute of Fuel Cell, Department of Automation, Shanghai Jiao Tong University, Shanghai 200030, China
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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.

Key words： Bombyx mori      MicroRNA      bmo-miR-0001      bmo-miR-0015      BmFib-L      Regulation of expression     
Received: 23 March 2006     
CLC:  TP273.3  
  TP183  
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CHEN Yue-hua
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ZHU Xin-jian
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CHEN Yue-hua, CAO Guang-yi, ZHU Xin-jian. LS-SVM model based nonlinear predictive control for MCFC system. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2007, 8(5): 748-754.

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http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.2007.A0748     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2007/V8/I5/748

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