Affiliations: [a] Electrical Engineering College, Henan University of Science and Technology, Luoyang, China, | [b] Information Engineering College, Henan University of Science and Technology, Luoyang, China
Correspondence:
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Corresponding author: Wenshao Bu, Electrical Engineering College, Henan University of Science and Technology, Kaiyuan Road No. 263, Luolong District, Luoyang, Henan, 471023, China. E-mail: [email protected]
Abstract: As for the inverse decoupling control system of a bearingless induction motor (BL-IM), in order to eliminate the influence of rotor resistance variation on its control performance, on the basis of the reactive power calculation of torque system, a novel fuzzy model reference adaptive (MRAS) identification method of rotor resistance is proposed. The reference model and adjustable model of instantaneous reactive power are derived in detail. In order to improve the identification performance of rotor resistance, a fuzzy PI adaptive law based on popov super stability theory is constructed. On this basis, a rotor resistance identifier is constructed, and it is used to on-line correct the rotor resistance parameter in the inverse system mathematical model of a BL-IM system. Based on the inverse decoupling control system of a BL-IM, the simulation experimental analysis and verification are carried out. The simulation experimental results have shown that when the proposed identification method of rotor resistance is used, not only the identification- and tracking-speed of rotor resistance can be effectively improved, but also the identification accuracy of rotor resistance can be improved; as for the BL-IM system, after the rotor resistance parameter is on-line corrected, not only the inverse dynamic decoupling control performance can be effectively improved, but also the robustness of BL-IM system to the variation of rotor resistance parameters can be improved.
Keywords: Bearingless induction motor, instantaneous reactive power, MRAS rotor resistance identification, fuzzy PI adaptive law, inverse system decoupling control
