Abstract
A nonlinear predictive control algorithm based on fuzzy model is presented for a family of complex system with severe nonlinearity such as Proton exchange membrane fuel cell (PEMFC). In order to implement nonlinear predictive control of the plant, the fuzzy model is identified by learning offline and rectified online. The model parameters are initialized by fuzzy clustering, and learned using back-propagation algorithm offline. If necessary, it can be rectified online to improve the predictive precision in the process of real-time control. Based on the obtained model, discrete optimization of the control action is carried out according to the principle of Branch and Bound (B&B) method. The test results demonstrate the effectiveness and advantage of this approach
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References
Cheng, K.H., Wang, Q.: A Branch and Bound Algorithm for the Traveling Purchaser Problem. European Journal of Operational Research 97(3), 571–579 (1997)
Liu, B., Shen, Q., Su, H.Y., Chu, J.: A Nonlinear Predictive Control Algorithm Based on Fuzzy Online Modeling and Discrete Optimization. In: IEEE International Conference on Systems, Man & Cybernetics, Washington, D.C., USA, October 5–8 (2003)
Wolkenhauer, O.: Fuzzy Clustering [Online]. Available: http://www.sbi.uni-rostock.De/data_engineering/clustering.pdf
Tomohiro, T., Michio, S.: Fuzzy Identification of System and Its Applications to Modeling and Control [J]. IEEE Transaction on Systems Man Cybernet 15(1), 16–32 (1985)
Costamagna, P., Srinivasan, S.: Quantum Jumps in the PEMFC Science and Technology from the 1960s to the Year 2000[J]. J. Power Sources 102, 253–269 (2001)
Berning, T., Lu, D.M., Djiali, N.: Three-Dimensional Computation Analysis of Transport Phenomena in a PEM Fuel Cell [J]. J. Power Sources 106, 284–294 (2002)
Wang, L.X.: Adaptive Fuzzy Systems and Control: Design and Stability. Prentice-Hall, Englewood Cliffs (1994)
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© 2004 Springer-Verlag Berlin Heidelberg
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Li, X., Fu, Xw., Cao, Gy., Zhu, Xj. (2004). Fuzzy Predictive Control Based on PEMFC Stack. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks - ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28648-6_23
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DOI: https://doi.org/10.1007/978-3-540-28648-6_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22843-1
Online ISBN: 978-3-540-28648-6
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