2023
DOI: 10.1109/tie.2022.3176279
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Reduced-Sensor-Based Multistage Model Reference Adaptive Control of PV-Fed PMSM Drive for Water Pump

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Cited by 9 publications
(10 citation statements)
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“…Traditional identification schemes include recursive least square (RLS) method, extended Kalman filter (EKF), and model reference adaptive (MRA) method. [49][50][51][52][53] RLS requires a lot of computing and storage space. The problem of adaptive rule design is complicated in MRA.…”
Section: Introductionmentioning
confidence: 99%
“…Traditional identification schemes include recursive least square (RLS) method, extended Kalman filter (EKF), and model reference adaptive (MRA) method. [49][50][51][52][53] RLS requires a lot of computing and storage space. The problem of adaptive rule design is complicated in MRA.…”
Section: Introductionmentioning
confidence: 99%
“…Researcher [11]- [13] proposed a new model 'Semi-Modular Dual-Stack' (SMDS) Motor ST BLDC with 3D-FEM parameters. Photovoltaic (PV) powered submersible electric water pumps are becoming popular in remote areas, due to the unavailability of a PLN source.…”
Section: Introductionmentioning
confidence: 99%
“…However, its energy consumption is significant compared to other machinery [1]. Therefore, researchers like [1] propose improving the mechanical pump design, while others suggest replacing the IM with more efficient permanent magnet synchronous motors (PMSMs) [2][3][4][5][6]. This manuscript focuses on moving centrifugal pumps with PMSMs.…”
Section: Introduction 1motivationsmentioning
confidence: 99%
“…Here, centrifugal pumps driven by PMSMs have a 5%, 8%, and 10% higher efficiency than those driven by IMs for flow rates of 100 m 3 /h at 100%, 80%, and 60% speeds, respectively. The works [3,4] propose customizing PMSM design for this application, while [5,6] study a variable speed PMSM for water pumps powered by an AC-AC converter fed by photovoltaic panels. The works [5,6] use a two-level voltage source inverter controlled by model reference adaptive control (MRAC).…”
Section: Introduction 1motivationsmentioning
confidence: 99%
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