Fractional-Order Controller Design and Analysis of SEPIC Converter

  • S. Jeyasudha
  • B. Geethalakshmi
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 446)


In this work, the fractional-order PI (FOPI) controller has been proposed for a single-ended primary inductance converter (SEPIC). The state-space model of the converter has been developed using the state equations of the SEPIC under different operating modes. The traditional PI controller has been designed using Ziegler–Nichols method, and the performance analysis is compared with the designed FOPI controller. Both PI and FOPI controller parameters are optimized by the genetic algorithm (GA). Simulation results of FOPI-controlled SEPIC show the better result and improved performance.


Fractional-order proportional integral controller Single-ended primary inductance converter Genetic algorithm Proportional integral controller Ziegler–Nichols tuning rule 


  1. 1.
    Ajami A, Ardi H, Farakhor A (2014) Design, analysis and implementation of a buck-boost DC/DC converter. IET Power Electron 7(12):2902–2913Google Scholar
  2. 2.
    Adhikari N, Singh B, Vyas AL (2011) Performance evaluation of a low power solar-PV energy system with SEPIC converter. In: IEEE Ninth international conference on power electronics and drive systems, Singapore, pp 763–769Google Scholar
  3. 3.
    El Khateb AH, Rahim NA, Selvaraja J (2013) Fuzzy logic control approach of a maximum power point employing SEPIC converter for standalone photovoltaic System. Procedia Environ Sci 17:529–536Google Scholar
  4. 4.
    Baiyu O, Lei S, Chunlei C (2010) Tuning of fractional PID controllers by using radial basis function neural networks. In: 8th IEEE international conference on control and automation Xiamen, ChinaGoogle Scholar
  5. 5.
    Maâmar B, Rachid M (2014) IMC-PID-fractional-order-filter controllers design for integer order systems. ISA Trans 53:1620–1628CrossRefGoogle Scholar
  6. 6.
    Cao JY, Cao KY (2006) Design of fractional order controllers based on particle swarm optimization. In: 1st IEEE conference on industrial electronics and applications, pp 1–6Google Scholar
  7. 7.
    Samanta S (2014) Genetic algorithm: an approach for optimization. Int J Latest Trends Eng Technol 3(3)Google Scholar
  8. 8.
    Ortiz-Lopez MG, Leyva-Ramos J, Carbajal-Gutierrez EE, Morales-Saldana JA (2008) Modelling and analysis of switch-mode cascade converters with a single active switch. IET Power Electron 1(4):478–487CrossRefGoogle Scholar
  9. 9.
    Ogata K (2001) Modern control engineering. New Jersey, Prentice-Hall (4th edn)Google Scholar
  10. 10.
    Podlubny I (1999) Fractional-order systems and PIλDμ controllers. IEEE Trans Autom Control, 208–214Google Scholar
  11. 11.
    Golderberg DE (1989) Genetic algorithm in search optimization and machine learning, reading. Addison-Wesley, MAGoogle Scholar
  12. 12.
    Matlab Help Documentation (2010) Global optimization toolbox user’s guide. The MathWorks Inc.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Pondicherry Engineering CollegePuducherryIndia

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