4.8 Article

Reduced-Sensor-Based Multistage Model Reference Adaptive Control of PV-Fed PMSM Drive for Water Pump

期刊

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
卷 70, 期 4, 页码 3782-3792

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2022.3176279

关键词

Multistage model reference adaptive control (MS-MRAC); permanent magnet synchronous motor (PMSM); pump; PV array; PV current sensor elimination

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Typically, a current sensor and encoder are used in a PV array fed PM synchronous motor based water pumping system for MPPT and rotor speed estimation, respectively. This article presents a multistage model reference adaptive control (MS-MRAC) for encoderless operation, which eliminates the need for these sensors. The MS-MRAC is a three-stage structure that estimates motor speed, resistance, and PM flux linkages. The effectiveness of this control technique is demonstrated through simulation and experimental validation.
Typically, photovoltaic (PV) array fed permanent magnet (PM) synchronous motor based water pumping system uses a current sensor to realize maximum power point tracking (MPPT) of PV array, and an encoder to obtain rotor speed. These sensors reduce reliability and increases cost of system. Besides, they are sensitive to both the temperature and electromagnetic noise. This necessitates the elimination of both the PV current sensor and encoder from the system. Thus, first, a multistage model reference adaptive control (MS-MRAC) for encoderless operation of system is presented in this article. The MS-MRAC is a three-stage structure wherein motor speed is estimated by first-stage, while resistance and PM flux linkages are estimated by the remaining two stages. Thus, the MS-MRAC is independent of motor parameters like resistance and PM flux linkages unlike conventional MRAC. Then, the motor speed as estimated by MS-MRAC is used to estimate PV array power, which along with PV voltage is used to realize MPPT, thereby eliminating PV current sensor. The effectiveness of presented control technique is shown through simulated results followed by their experimental validation under different operating scenarios.

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