Optimal Control of Proton Exchange Membrane Fuel Cell Based on Particle Swarm Optimization and Genetic Algorithm
Abstract
Since the operation of a Proton Exchange Membrane Fuel Cell (PEMFC) is extremely nonlinear process as well as its parameters change when it is operating, a designer can’t easily to control it; accordingly conventional controllers cannot satisfy the control objectives as well as the intelligent controllers. Thus, in this paper an intelligent controller is proposed for fuel cell stack control system based on Particle Swarm Optimization (PSO). In order to analyze the efficiency of this method, the results are compared with other intelligent controller based on Genetic Algorithm (GA). The simulation results demonstrate the high performance capability of both proposed controllers in terms of precise and convergence speed
Keywords
Intelligent controller Genetic Algorithm Particle swarm optimization Proton exchange membrane fuel cell
References
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- T. Sun, S.J. Yan, G.Y. Cao, X.J. Zhu, “Modeling and control PEMFC using fuzzy neural network,” J. Zhejiang, University science, vol. 6, pp.1084-1089, 2005.
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- K.S. Narendra, S. Mukhopadhyay, “Adaptive control using neural networks and approximate models,” IEEE Trans, neural networks, vol. 8, pp. 1103-1112, 1997.
- R.C. Eberhart, J. Kennedy, “Anew optimizer using particle swarm theory,” IEEE, Service center, pp. 39-43, 1995.
- D.E. Goldberg,”Genetic algorithms in search, optimization and machine learning,” Addison-Wesley, Reading, MA, 1989.
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Abstract
References
- J.M. Correa, F.A. Farret, L.N. Canha, M.G. Simoes, “An electrochemical-based fuel cell model suitable for electrical engineering automation approach,” IEEE Trans, Ind, Electron, vol. 51, pp. 1103-1112, 2004.
- T. Sun, S.J. Yan, G.Y. Cao, X.J. Zhu, “Modeling and control PEMFC using fuzzy neural network,” J. Zhejiang, University science, vol. 6, pp.1084-1089, 2005.
- Z.D. Zhong. X.J. Zhu, G.A. Cao, “Modeling a PEMFC by support vector machine,” J. power source, vol. 160, pp. 293-298, 2006.
- K.S. Narendra, S. Mukhopadhyay, “Adaptive control using neural networks and approximate models,” IEEE Trans, neural networks, vol. 8, pp. 1103-1112, 1997.
- R.C. Eberhart, J. Kennedy, “Anew optimizer using particle swarm theory,” IEEE, Service center, pp. 39-43, 1995.
- D.E. Goldberg,”Genetic algorithms in search, optimization and machine learning,” Addison-Wesley, Reading, MA, 1989.
- M. Cirrincione, M. Pucci, G. Cirrincione, M.G. Simoes, “A neural non-linear predictive control for PEM-FC,” J. Electrical system, vol. 1-2. pp. 1-18, 2005.
Details
| Other ID | JA65GN45CE |
|---|---|
| Journal Section | Articles |
| Authors | |
| Publication Date | September 1, 2009 |
| Published in Issue | Year 2009 Volume: 1 Issue: 3 |