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Robust Optimized Artificial Neural Network Based PEM Fuelcell Voltage Tracking

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Innovations in Bio-Inspired Computing and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 424))

Abstract

Voltage control of Proton Exchange Membrane Fuel Cell (PEMFC) is necessary for any practical application. This paper considers a state space model for controller design and a Neural Network (NN) feed forward controller with an optimization technique called Harmony Search algorithm is considered to control the output voltage. This paper compares the results of the proposed controller with the NN feed forward controller. The comparison shows the proposed controller follows the reference voltage more closely than NN feed forward controller. Finally the performance of the controller is studied by evaluating Integral Squared Error (ISE), Integral Absolute Error (IAE) and Integral Time-weighted Absolute Error (ITAE) and the results are compared. The system error of the proposed controller is reduced to a least minimum value compared with the other.

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Authors and Affiliations

  1. Anna University, Chennai, India

    R. Vinu & Paul Varghese

Authors
  1. R. Vinu
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  2. Paul Varghese
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Corresponding author

Correspondence to R. Vinu .

Editor information

Editors and Affiliations

  1. Dep. of Computer Science, VŠB – Technical Univ. of Ostrava, Ostrava, Czech Republic

    Václav Snášel

  2. (MIR Labs), Scientific Net Innov & Res Excel, Auburn, Washington, USA

    Ajit Abraham

  3. Faculty of Elec. Eng. & Comp. Sci., VÅ B - Technical University of Ostrava, Ostrava-Poruba, Czech Republic

    Pavel Krömer

  4. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Millie Pant

  5. Fac of Info & Comm, Comp Inte & Tech Lab, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia

    Azah Kamilah Muda

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Vinu, R., Varghese, P. (2016). Robust Optimized Artificial Neural Network Based PEM Fuelcell Voltage Tracking. In: Snášel, V., Abraham, A., Krömer, P., Pant, M., Muda, A. (eds) Innovations in Bio-Inspired Computing and Applications. Advances in Intelligent Systems and Computing, vol 424. Springer, Cham. https://doi.org/10.1007/978-3-319-28031-8_7

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  • DOI: https://doi.org/10.1007/978-3-319-28031-8_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28030-1

  • Online ISBN: 978-3-319-28031-8

  • eBook Packages: EngineeringEngineering (R0)

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