FOPID Controller Design for a Buck Converter System Using a Novel Hybrid Cooperation Search Algorithm with Pattern Search for Parameter Tuning

Year 2023, , 417 - 441, 31.12.2023

Cihan Ersalı , Baran Hekimoğlu

https://doi.org/10.54287/gujsa.1357216

Abstract

This research introduces a novel metaheuristic algorithm, OCSAPS, representing an upgraded cooperation search algorithm (CSA) version. OCSAPS incorporates opposition-based learning (OBL) and pattern search (PS) algorithms. The proposed algorithm's application aims to develop a fractional order proportional-integral-derivative (FOPID) controller tailored for a buck converter system. The efficacy of the proposed algorithm is assessed by statistical boxplot and convergence response analyses. Furthermore, the performance of the OCSAPS-based FOPID-controlled buck converter system is benchmarked against CSA, Harris hawk optimization (HHO), and genetic algorithm (GA). This comparative analysis encompasses transient and frequency responses, performance indices, and robustness analysis. The outcomes of this comparison highlight the distinctive advantages of the proposed approach-based system. Moreover, the proposed approach's performance was compared with six other approaches used to control buck converter systems similarly regarding both time and frequency domain responses. Overall, the findings underscore the efficacy of the OCSAPS algorithm as a robust solution for designing FOPID controllers in buck converter systems.

Keywords

FOPID Controller, Buck Converter, Cooperation Search Algorithm, Pattern Search, Opposition-Based Learning

Ethical Statement

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supporting Institution

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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