Open AccessFractional‐order fuzzy PID controller design on buck converter with antlion optimization algorithm
Author(s) -
Ghamari Seyyed Morteza,
Narm Hossein Gholizade,
Mollaee Hasan
Publication year - 2022
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/cth2.12230
Subject(s) - pid controller , control theory (sociology) , robustness (evolution) , matlab , computer science , fuzzy logic , parametric statistics , control engineering , algorithm , mathematics , engineering , temperature control , control (management) , biochemistry , chemistry , statistics , artificial intelligence , gene , operating system
The design of a Fractional‐Order fuzzy‐based PID (FO‐F‐PID) control structure is presented for Buck converter in the presence of harmful disturbances. A fractional‐order proportional‐integral‐derivative (FO‐PID) control scheme is utilized initially to damp the oscillations and remove the steady‐state error. To increase the tendency rate of the error to zero, the FO‐PID method is applied to a fuzzy‐logic‐based compensatory stage. At the same time, the fuzzy part gathers the data based on the error and error derivative. The FO‐PID control scheme has the capability to enhance the robustness of the control technique against disturbances and parametric variations. Furthermore, to optimize the control parameters, an efficient algorithm so‐called Antlion Optimization (ALO) algorithm, is used. Utilizing the ALO algorithm for tuning the FO‐PID gains depicts more accurate responses in solving constrained problems with diverse search spaces. Considering numerous disturbances on DC‐DC converters, an FO‐F‐PID controller can be an appropriate alternative since it is more robust against load variations and noise. Moreover, PSO‐PID and FO‐PSO‐PID controllers are designed to drive a comparison between them. Finally, the merits of the presented controller are validated for various scenarios. It can be seen that the FO‐F‐ALO‐PID method provides much better results with faster dynamics. Matlab‐Simulink environment is used for the simulations, and the experimental results are tested by the micro‐processor to validate the superiority of the proposed method.