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Neural Computing and Applications

, Volume 31, Issue 8, pp 4137–4155 | Cite as

Efficient control of integrated power system using self-tuned fractional-order fuzzy PID controller

  • K. Nithilasaravanan
  • Nitisha Thakwani
  • Puneet Mishra
  • Vineet KumarEmail author
  • K. P. S. Rana
Original Article

Abstract

The integrated power system (IPS) uses various autonomous generation and energy storage systems like aqua electrolyzer, battery, diesel engine, flywheel, fuel cell, solar photovoltaic, ultracapacitor, wind turbine, etc. These may be switched on/off and may run at higher/lower power outputs, at different times. Additionally, IPS is also subjected to parameter variations of its components and the load. As a result, the frequency of an IPS fluctuates from the nominal desired value and therefore it requires a robust controller to accomplish the above-mentioned task. In this work, a self-tuned fractional-order fuzzy PID (STFOFPID) controller, tuned using cuckoo search algorithm, is investigated for efficient control of IPS. STFOFPID is essentially a Takagi–Sugeno model-based fuzzy adaptive controller comprising of non-integer-order differ-integral operators. To assess the relative performance of STFOFPID controller, it is compared with its integer-order counterpart on the basis of their respective objective function value defined as the sum of integral of squared error and integral of squared deviation of controller output. Intensive LabVIEW-based simulation studies have indicated the robustness and hence superiority of STFOFPID controller over its integral counterpart.

Keywords

Self-tuned fractional-order fuzzy PID controller Integrated power system Renewable energy generation Efficient control Robust control Cuckoo search algorithm 

Notes

Compliance with ethical standards

Conflict of interest

The authors certify that they have NO affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.

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Copyright information

© The Natural Computing Applications Forum 2018

Authors and Affiliations

  • K. Nithilasaravanan
    • 1
  • Nitisha Thakwani
    • 1
  • Puneet Mishra
    • 2
  • Vineet Kumar
    • 1
    Email author
  • K. P. S. Rana
    • 1
  1. 1.Division of Instrumentation and Control EngineeringNetaji Subhas Institute of TechnologyNew DelhiIndia
  2. 2.Department of Electronics and Communication EngineeringGLA UniversityMathuraIndia

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