Mateusz Dybkowski

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This paper deals with an analysis of the vectorcontrolled induction-motor (IM) drive with a novel model reference adaptive system (MRAS)-type rotor speed estimator. A stability-analysis method of this novel MRAS estimator is shown. The influence of equivalent-circuit parameter changes of the IM on the pole placement of the estimator transfer function and(More)
In this paper, the concept of a model reference adaptive control of a sensorless induction motor (IM) drive with elastic joint is proposed. An adaptive speed controller uses fuzzy neural network equipped with an additional option for online tuning of its chosen parameters. A sliding-mode neuro-fuzzy controller is used as the speed controller, whose(More)
In the paper two types of speed, torque and flux estimators are described. The Sliding Mode Observer (SMO) and the Model Reference Adaptive System (MRAS) type estimators are applied in the sensorless Direct Torque Control with Space Vector Modulation algorithm (DTC-SVM) of Induction Motor (IM) drive. Dynamical performance of the drive and the estimator(More)
In the paper an analysis of the Direct Field Control of induction motor drive with broken rotor bars is presented. A drive system with and without a mechanical speed sensor is analyzed. In the sensorless induction motor (IM) drive the rotor flux and speed is reconstructed with the use of a MRAS estimator, where the induction motor is used as a reference(More)
This paper discusses a model reference adaptive sliding-mode control of the sensorless vector controlled induction motor drive in a wide speed range. The adaptive speed controller uses on-line trained fuzzy neural network, which enables very fast tracking of the changing speed reference signal. This adaptive sliding-mode neuro-fuzzy controller (ASNFC) is(More)
In this paper a performance analysis of the speed sensorless Direct Rotor-Field Control (DRFOC) structure of the induction motor (IM) drive with rotor faults and disturbance in DC-bus voltage conditions is presented. In the sensorless IM drive the rotor flux and speed is reconstructed using the MRAS<sup>CC</sup> estimator, where the induction motor is used(More)
In the paper a model reference adaptive sliding-mode control using on-line trained fuzzy neural network is applied to the sensorless induction motor drive system with MRAS type speed estimator. In this control structure adaptive sliding-mode neuro-fuzzy controller (ASNFC) is used as a speed controller, in the direct field oriented control structure.(More)
In this paper the Fault Tolerant (FT) vector controlled induction motor drive system is described and tested in various drive conditions. The influence of the rotor speed sensor faults on the properties of the analyzed drive are tested. Faults detection algorithms, based on different algorithms are developed and described. The results of the simulation(More)