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Fuzzy Logic Controller and Neural Network Controller as a Power System Regulator Implemented on GUI

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Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 130))

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Abstract

This paper presents design of Fuzzy Logic Controller (FLC) and Neural Network Controller (NNC) as a Regulator for effective voltage control over a Simple and a Stabilized regulator in order to maintain stability and enhance the closed-loop performance of a power system using a fast computing user friendly Graphical User Interface(GUI). The gains and tuning parameters are kept almost same in Simple, Stabilized, Fuzzy Logic and Neural Network Regulator. The step responses are interfaced on a common GUI page, the performance of Fuzzy Logic Regulator in comparison to the conventional fixed gain regulators proves better but Neural Network Controller has the best results.

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References

  1. Kunder, P.: Power System Stability and Control. McGraw, Hill, New York (2001)

    Google Scholar 

  2. Larsen, E.V., Swann, D.A.: Applying Power System Stabilizers Part I-III. IEEE Transactions on Power Apparatus and Systems PAS-100(6), 3017–3041 (1981)

    Article  Google Scholar 

  3. Hadisaadat: Power System Analysis. Tata McGraw, Hill (2002)

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  4. Matlab 2008- Control system toolbox, Fuzzy Logic Toolbox, Neural Network Toolbox

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  5. Ghoshal, S.P.: Optimization of PID gains by particle swarm optimization in fuzzy based automatic generation control. Electr. Power Syst. Res. 72203–72212 (2004)

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  6. Gaing, Z.L.: A particle swarm optimization approach for optimum design of PID controller in AVR system. IEEE Trans. Energy Convers. 19, 384–391 (2004)

    Article  Google Scholar 

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Correspondence to Parita D. Giri .

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© 2012 Springer India Pvt. Ltd.

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Giri, P.D., Shah, S.K. (2012). Fuzzy Logic Controller and Neural Network Controller as a Power System Regulator Implemented on GUI. In: Deep, K., Nagar, A., Pant, M., Bansal, J. (eds) Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011. Advances in Intelligent and Soft Computing, vol 130. Springer, India. https://doi.org/10.1007/978-81-322-0487-9_24

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  • DOI: https://doi.org/10.1007/978-81-322-0487-9_24

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  • Publisher Name: Springer, India

  • Print ISBN: 978-81-322-0486-2

  • Online ISBN: 978-81-322-0487-9

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