INTELLIGENT ELECTRIC DRIVE CONTROL SYSTEMS AND ARTIFICIAL INTELLIGENCE: AN IN-DEPTH REVIEW

dc.contributor.authorBekzod Obidov
dc.date.accessioned2025-12-29T14:43:51Z
dc.date.issued2024-09-09
dc.description.abstractThis paper presents a comprehensive review of intelligent electric drive control systems (IEDCS) and the role of artificial intelligence (AI) in their development and optimization. As the demand for more efficient, reliable, and intelligent electric drives grows, integrating AI techniques such as machine learning, neural networks, and fuzzy logic has emerged as a transformative solution. These advancements not only enhance control accuracy but also enable predictive maintenance, fault detection, and adaptive control, leading to improved performance in various industrial and automotive applications. This review explores the evolution of IEDCS, highlighting key technologies, design methodologies, and AI-driven algorithms that have revolutionized electric drive systems. It also discusses current challenges, potential improvements, and future trends in the integration of AI with electric drive controls, offering insights into the next generation of intelligent systems.
dc.formatapplication/pdf
dc.identifier.urihttps://webofjournals.com/index.php/3/article/view/1742
dc.identifier.urihttps://asianeducationindex.com/handle/123456789/22524
dc.language.isoeng
dc.publisherWeb of Journals Publishing
dc.relationhttps://webofjournals.com/index.php/3/article/view/1742/1722
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0
dc.sourceWeb of Discoveries: Journal of Analysis and Inventions; Vol. 2 No. 9 (2024): WOD; 1-6
dc.source2938-3773
dc.subjectIntelligent electric drive control systems, artificial intelligence, machine learning, deep learning, neural networks, fuzzy logic control, reinforcement learning, predictive maintenance, edge computing, autonomous systems.
dc.titleINTELLIGENT ELECTRIC DRIVE CONTROL SYSTEMS AND ARTIFICIAL INTELLIGENCE: AN IN-DEPTH REVIEW
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typePeer-reviewed Article

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