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A real-time estimator of electrical parameters for vector controlled induction motor using a reduced order extended Kalman filter

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Detalhes bibliográficos
Resumo:This paper presents an application of the extended Kalman filter (EKF) to the simultaneous on-line estimation of the dq rotor flux components and all the electrical parameters of a vector controlled induction motor. A time-discrete reduced order model structure is deduced and presents a simple and reduced state equation and a scalar output equation. This approach, combined with the use of the rotor reference frame, offers advantages for real-time identification, compared with full order models, because it reduces the computational cost. The proposed new approach requires the measurement of motor speed, stator voltages and currents signals. Simulation and experimental studies presented in this paper highlight the improvements produced by this new approach based on the extended Kalman filter and a new discretization technique, under real operation conditions.
Autores principais:Leite, V.
Outros Autores:Araújo, Rui Esteves; Freitas, Diamantino Silva
Assunto:Induction motors Estimation techniques Variable speed drives Adaptive control
Ano:2002
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB
Descrição
Resumo:This paper presents an application of the extended Kalman filter (EKF) to the simultaneous on-line estimation of the dq rotor flux components and all the electrical parameters of a vector controlled induction motor. A time-discrete reduced order model structure is deduced and presents a simple and reduced state equation and a scalar output equation. This approach, combined with the use of the rotor reference frame, offers advantages for real-time identification, compared with full order models, because it reduces the computational cost. The proposed new approach requires the measurement of motor speed, stator voltages and currents signals. Simulation and experimental studies presented in this paper highlight the improvements produced by this new approach based on the extended Kalman filter and a new discretization technique, under real operation conditions.