Mounir Bensaid, A. Ba-Razzouk, Mustapha El Haroussi
{"title":"利用 ADALINE 算法和级联滑模控制缓解多电机系统电压骤降效应的管理策略","authors":"Mounir Bensaid, A. Ba-Razzouk, Mustapha El Haroussi","doi":"10.11591/ijpeds.v15.i1.pp239-250","DOIUrl":null,"url":null,"abstract":"Multi-motor systems (MMS) find widespread use in various industrial applications, including plastic, paper, textiles, and steel rolling mills, where synchronized speeds are crucial for optimal operation. However, a significant limitation of these systems is their susceptibility to voltage sags, resulting in speed and synchronization loss, along with peak currents and torques during voltage recovery. This paper presents a comprehensive multi-motors management strategy aimed at attenuating the adverse effects of voltage sags. The proposed technique is based on principles that involve recovering the system’s kinetic energy and leveraging the current reversibility of the converters. The control scheme comprises two main strategies: an adaptive linear neuron or later adaptive linear element (ADALINE)-based voltage sag detection algorithm utilizing least mean square (LMS) adaptation for rapid convergence using artificial neural networks, and a control scheme incorporating sliding mode speed controllers and indirect rotor field-oriented control (IRFOC). Additionally, a logic-based strategy for voltage sag attenuation completes the control framework. The effectiveness and efficiency of the proposed strategy are demonstrated through simulation results obtained using MATLAB/Simulink/SimPowerSystems.","PeriodicalId":355274,"journal":{"name":"International Journal of Power Electronics and Drive Systems (IJPEDS)","volume":"80 21","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Management strategy to mitigate voltage sags effects of a multi-motors system using ADALINE algorithm and cascade sliding mode control\",\"authors\":\"Mounir Bensaid, A. Ba-Razzouk, Mustapha El Haroussi\",\"doi\":\"10.11591/ijpeds.v15.i1.pp239-250\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multi-motor systems (MMS) find widespread use in various industrial applications, including plastic, paper, textiles, and steel rolling mills, where synchronized speeds are crucial for optimal operation. However, a significant limitation of these systems is their susceptibility to voltage sags, resulting in speed and synchronization loss, along with peak currents and torques during voltage recovery. This paper presents a comprehensive multi-motors management strategy aimed at attenuating the adverse effects of voltage sags. The proposed technique is based on principles that involve recovering the system’s kinetic energy and leveraging the current reversibility of the converters. The control scheme comprises two main strategies: an adaptive linear neuron or later adaptive linear element (ADALINE)-based voltage sag detection algorithm utilizing least mean square (LMS) adaptation for rapid convergence using artificial neural networks, and a control scheme incorporating sliding mode speed controllers and indirect rotor field-oriented control (IRFOC). Additionally, a logic-based strategy for voltage sag attenuation completes the control framework. The effectiveness and efficiency of the proposed strategy are demonstrated through simulation results obtained using MATLAB/Simulink/SimPowerSystems.\",\"PeriodicalId\":355274,\"journal\":{\"name\":\"International Journal of Power Electronics and Drive Systems (IJPEDS)\",\"volume\":\"80 21\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Power Electronics and Drive Systems (IJPEDS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.11591/ijpeds.v15.i1.pp239-250\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Power Electronics and Drive Systems (IJPEDS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11591/ijpeds.v15.i1.pp239-250","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Management strategy to mitigate voltage sags effects of a multi-motors system using ADALINE algorithm and cascade sliding mode control
Multi-motor systems (MMS) find widespread use in various industrial applications, including plastic, paper, textiles, and steel rolling mills, where synchronized speeds are crucial for optimal operation. However, a significant limitation of these systems is their susceptibility to voltage sags, resulting in speed and synchronization loss, along with peak currents and torques during voltage recovery. This paper presents a comprehensive multi-motors management strategy aimed at attenuating the adverse effects of voltage sags. The proposed technique is based on principles that involve recovering the system’s kinetic energy and leveraging the current reversibility of the converters. The control scheme comprises two main strategies: an adaptive linear neuron or later adaptive linear element (ADALINE)-based voltage sag detection algorithm utilizing least mean square (LMS) adaptation for rapid convergence using artificial neural networks, and a control scheme incorporating sliding mode speed controllers and indirect rotor field-oriented control (IRFOC). Additionally, a logic-based strategy for voltage sag attenuation completes the control framework. The effectiveness and efficiency of the proposed strategy are demonstrated through simulation results obtained using MATLAB/Simulink/SimPowerSystems.