Disturbance rejecting PID-FF controller design of a non-ideal buck converter using an innovative snake optimizer with pattern search algorithm.

Disturbance rejection Non-ideal buck converter Opposition-based learning PID-FF controller Pattern search Pole placement Snake optimizer algorithm

Journal

Heliyon
ISSN: 2405-8440
Titre abrégé: Heliyon
Pays: England
ID NLM: 101672560

Informations de publication

Date de publication:
30 Jul 2024
Historique:
received: 23 04 2024
revised: 29 06 2024
accepted: 09 07 2024
medline: 31 7 2024
pubmed: 31 7 2024
entrez: 31 7 2024
Statut: epublish

Résumé

The optimal design of a proportional-integral-derivative controller with two cascaded first-order low-pass filters (PID-FF) for non-ideal buck converters faces significant challenges, including effective disturbance rejection, robustness to parameter variations, and the mitigation of high-frequency signal noise, with existing approaches often struggling and leading to suboptimal performance in practical applications. This study addresses these challenges by introducing a constraint on the open-loop crossover frequency to mitigate high-frequency noise and ensuring the controller prioritizes maintaining constant output voltage and robust responsiveness to input voltage and load current variations. This study also introduces an innovative metaheuristic algorithm, the opposition-based snake optimizer with pattern search (OSOPS), designed to address these limitations. OSOPS enhances the Snake Optimizer (SO) by integrating opposition-based learning (OBL) and Pattern Search (PS), thereby improving its exploration and exploitation capabilities. The proposed algorithm design includes a crossover frequency constraint aimed at counteracting high-frequency noise and ensuring robust performance under diverse disturbances. The efficacy of the OSOPS algorithm is demonstrated through rigorous statistical box plot analysis and convergence response comparisons with the original SO algorithm. Additionally, we systematically compare the performance of the OSOPS-based PID-FF-controlled non-ideal buck converter system against systems utilizing the original SO algorithm and the classical pole placement (PP) method. This evaluation encompasses transient and frequency responses, disturbance rejection, and robustness analysis. The results reveal that the OSOPS-based system outperforms the SO- and PP-based systems with 14.21 % and 32.10 % faster rise times, along with 15.38 % and 84.95 % faster settling times, respectively. The OSOPS and SO systems also exhibit higher bandwidths, exceeding the PP-based system by 18.74 % and 17.03 %, respectively. By addressing the key challenges in PID-FF controller design for non-ideal buck converters, this study provides a substantial advancement in control strategy, promising enhanced performance in practical applications.

Identifiants

pubmed: 39082008
doi: 10.1016/j.heliyon.2024.e34448
pii: S2405-8440(24)10479-3
pmc: PMC11284365
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e34448

Informations de copyright

© 2024 The Authors. Published by Elsevier Ltd.

Déclaration de conflit d'intérêts

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Cihan Ersali (C)

Department of Electrical and Electronics Engineering, Batman University, Batman, 72100, Turkey.

Baran Hekimoglu (B)

Department of Electrical and Electronics Engineering, Batman University, Batman, 72100, Turkey.

Musa Yilmaz (M)

Department of Electrical and Electronics Engineering, Batman University, Batman, 72100, Turkey.
Bourns College of Engineering, Center for Environmental Research and Technology, University of California at Riverside, Riverside, CA, 92521, USA.

Alfredo A Martinez-Morales (AA)

Bourns College of Engineering, Center for Environmental Research and Technology, University of California at Riverside, Riverside, CA, 92521, USA.
Winston Chung Global Energy Center, University of California at Riverside, Riverside, CA, 92521, USA.
Electrical and Computer Engineering Department, University of California at Riverside, Riverside, CA, 92521, USA.

Tahir Cetin Akinci (TC)

Winston Chung Global Energy Center, University of California at Riverside, Riverside, CA, 92521, USA.
Electrical Engineering Department, Istanbul Technical University, 34469, Istanbul, Turkey.

Classifications MeSH