2002
DOI: 10.1049/ip-epa:20020018
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Comparative study of a sliding-mode observer and Kalman filters for full state estimation in an induction machine

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Cited by 120 publications
(42 citation statements)
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“…Incorrect covariance matrices will reduce the robustness to parameter uncertainty and external noise [69]. The practical implementation of Extended Kalman Filter (EKF) involves significant numerical complexity [69]. The traditional sliding mode observer has no robustness to uncertainty in system parameters.…”
Section: Thesis Objectivesmentioning
confidence: 99%
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“…Incorrect covariance matrices will reduce the robustness to parameter uncertainty and external noise [69]. The practical implementation of Extended Kalman Filter (EKF) involves significant numerical complexity [69]. The traditional sliding mode observer has no robustness to uncertainty in system parameters.…”
Section: Thesis Objectivesmentioning
confidence: 99%
“…The Kalman filter robustness to parameter uncertainty depends on the accurate value of the process and the measurement noise covariance matrices. Incorrect covariance matrices will reduce the robustness to parameter uncertainty and external noise [69]. The practical implementation of Extended Kalman Filter (EKF) involves significant numerical complexity [69].…”
Section: Thesis Objectivesmentioning
confidence: 99%
“…And, in order to reduce torque ripple, the expected voltage vector linear combination are established by two adjacent non-zero switching voltage vectors and zero voltage vectors. Take the example of figure 2, when * s u is in sector I, the adjacent non-zero voltage vectors 4 U , 6 U and zero voltage vectors should be selected. The action time of the non-zero voltage vector and the zero vector as shown in formula (8).…”
Section: The Basic Principle Of Svpwm-dtcmentioning
confidence: 99%
“…In addition, sliding mode techniques have advantages over Kalman filter approaches for electric power systems. One of these advantages is that robustness of the sliding-mode observer to parameter uncertainties and external noise can be guaranteed [26,27]. State estimation and sliding mode control for a special class of stochastic dynamic systems, semi Markovian jump systems, is presented in [28].…”
Section: Introductionmentioning
confidence: 99%