Research on Displacement Sensorless Control for Bearingless Synchronous Reluctance Motor Based on the Whale Optimization Algorithm–Elman Neural Network

Autor:	Enxiang Xu, Ruijie Zhao
Jazyk:	angličtina
Rok vydání:	2024
Předmět:	bearingless synchronous reluctance motor Elman neural network whale optimization algorithm displacement sensorless Materials of engineering and construction. Mechanics of materials TA401-492 Production of electric energy or power. Powerplants. Central stations TK1001-1841
Zdroj:	Actuators, Vol 13, Iss 5, p 192 (2024)
Druh dokumentu:	article
ISSN:	13050192 2076-0825
DOI:	10.3390/act13050192
Popis:	The unique structure of bearingless motors requires extra displacement sensors to monitor rotor movement, unlike conventional synchronous motors. However, this requirement inevitably escalates the cost and size of the motor. To address these issues, this paper proposes a novel approach: a bearingless synchronous reluctance motor (BSRM) without displacement sensors, utilizing the whale optimization algorithm–Elman neural network (WOA-ENN). The paper firstly introduces the suspension mechanism and mathematical model of the BSRM, upon which a function containing rotor position information is constructed. Subsequently, a sensorless method based on Elman neural network (ENN) is proposed, optimized using the whale optimization algorithm (WOA). Finally, the feasibility and reliability of the proposed approach are validated through simulations and experiments.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/a8b7f3ea388044359cea9a8229fdeb3f Zobrazit plný text záznamu View record in DOAJ