Advanced Intelligent Methodologies for Power Electronic Converters

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".

Deadline for manuscript submissions: 31 January 2026 | Viewed by 279

Special Issue Editors


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Guest Editor
Department of Industrial Engineering, University of A Coruña, CTC, CITIC, Ferrol, 15071 A Coruña, Spain
Interests: knowledge engineering and expert systems for diagnosis and control; intelligent systems for modelling, optimization, and control; fault and anomaly detection using traditional and intelligent techniques; new sensors; robust sensors; virtual sensors
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of A Coruña, CTC, CITIC, Ferrol, 15071 A Coruña, Spain
Interests: modelling, optimization, and control based on intelligent systems; fault and anomaly detection based on traditional and intelligent techniques; artificial intelligence; power energy systems
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of A Coruña, CTC, CITIC, Ferrol, 15071 A Coruña, Spain
Interests: knowledge engineering and expert systems for diagnosis and control; intelligent systems for modelling, optimization, and control; anomaly detection using traditional and intelligent techniques; new sensors; robust sensors and virtual sensors; artificial intelligence; power energy systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid advancement of digital technologies and the growing complexity of modern electrical systems have led to a paradigm shift in the design and operation of power electronic converters. These converters play a crucial role in a wide range of applications, including renewable energy systems, electric vehicles, smart grids, and industrial automation. In order to meet increasing demands for higher efficiency, improved reliability, adaptability, and smart functionalities, there is a pressing need to integrate intelligent methodologies into the design, control, and optimization processes of these systems.

This Special Issue is dedicated to exploring the transformative impact of advanced intelligent techniques on power electronic converter technology. It aims to gather high-quality contributions that demonstrate how these techniques can significantly improve performance metrics such as dynamic response, fault tolerance, energy efficiency, and control robustness. Contributions that combine theoretical innovations with practical implementations, experimental validations, or industrial case studies are especially encouraged.

The goal of this Issue is to provide a comprehensive platform for researchers, engineers, and industry professionals to present the latest developments and emerging trends in intelligent power electronics. It will serve as both a reference and a source of inspiration for future innovations aimed at creating smarter, more efficient, and more resilient energy systems. By fostering interdisciplinary collaboration and showcasing state-of-the-art methodologies, this Special Issue aspires to contribute meaningfully to the advancement of next-generation power electronic technologies.

The following are examples of areas that this Special Issue hopes to advance:

  • AI/ML-based modeling and control of converters;
  • Intelligent fault detection and diagnostics;
  • Optimization algorithms for converter design;
  • Adaptive and predictive control strategies;
  • Real-time implementation and hardware-in-the-loop testing;
  • Intelligent power management and energy efficiency techniques;
  • Optimization and enhancement of system performance;
  • Use of intelligent systems;
  • Applications for intelligent control;
  • Development of novel intelligent control topologies and methodologies;
  • Modeling of complex systems;
  • Process and method improvement.

Dr. Jose Luis Calvo-Rolle
Dr. Francisco Zayas-Gato
Dr. Esteban Jove Pérez
Guest Editors

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Keywords

  • fault detection
  • diagnosis
  • control
  • intelligent systems
  • industrial electronics
  • power electronics
  • energy efficiency
  • power drivers

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Published Papers (1 paper)

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Research

23 pages, 5063 KB  
Article
Hippopotamus Optimization-Sliding Mode Control-Based Frequency Tracking Method for Ultrasonic Power Supplies with a T-Type Matching Network
by Linzuan Ye and Huafeng Cai
Electronics 2025, 14(17), 3358; https://doi.org/10.3390/electronics14173358 - 24 Aug 2025
Viewed by 193
Abstract
The ultrasonic power supply constitutes the core component of an ultrasonic welding system, and its main function is to convert the industrial frequency electricity into resonant high-frequency electricity in order to achieve mechanical energy conversion. However, factors such as changes in ambient temperature [...] Read more.
The ultrasonic power supply constitutes the core component of an ultrasonic welding system, and its main function is to convert the industrial frequency electricity into resonant high-frequency electricity in order to achieve mechanical energy conversion. However, factors such as changes in ambient temperature or component aging may cause the resonant frequency of the transducer to drift, thus detuning the resonant system and seriously affecting system performance. Therefore, an ultrasonic welding system requires high-frequency tracking in real time. Traditional frequency tracking methods (such as acoustic tracking, PID control, etc.) have defects such as poor stability, narrow bandwidth, or cumbersome parameter setting, making it difficult to meet the demand for fast tracking. To address these problems, this study adopts a T-matching network and utilizes sliding mode control for frequency tracking. In order to solve the problems of slow convergence and obvious jitter in sliding mode control (SMC), a Hippopotamus Optimization (HO) algorithm is introduced to simulate hippopotamuses’ group behavior and predation mechanisms, thereby optimizing the control parameters. It is verified through simulation that the SMC algorithm optimized by the HO algorithm (HO-SMC) is able to suppress frequency drift more effectively and demonstrates the advantages of fast response, high accuracy, and strong robustness in the scenario of sudden load changes. Full article
(This article belongs to the Special Issue Advanced Intelligent Methodologies for Power Electronic Converters)
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