This paper deals with the stability analysis of MRAS current speed estimator in a motoring and regenerating mode. The unstable operating points of the estimator, mainly in a regenerating mode are widely discussed. The expanded version of the estimator MRASCC is proposed to provide its stability in the whole operating range. The new correction coefficients for two analyzed stabilization methods are proposed. Finally, simulation results confirming the theoretical analysis are presented
This paper deals with the stability problem of three stator current error-based estimators of induction motor speed, especially in the regenerating operation mode. The stability of the adaptive full-order observer (AFO) and two model reference adaptive systems (MRASs) based on a stator current error (MRASCCand MRASCV) is briefly analysed, and the stability borders are determined and compared. It is shown that MRASCVspeed estimator is stable in the whole operation range including the regenerating mode without any modifications. The stability enhancement method for AFO and MRASCCestimators is described, and the solution for their stability improvement is proposed. Torque-speed characteristics of the analysed MRAStype estimators in a wide range of drive speed and load torque changes are given, as well as the behaviour of estimators during transients is compared. The theoretical analysis and simulation test results are validated by experimental tests.
The article presents the current state and development trends of electrical drives, with particular emphasis on modern control structures and safety systems of various types of electrical machines. Special attention was paid to the needs of industrial drive systems and a possibility of practical implementation of complex control algorithms. Development perspectives of electrical drives are discussed from the perspective of new trends in control, power electronics and electrical machines, with consideration given to systems robust to faults of drive system elements.
Murat Barut, Marko Hinkkanen and Teresa Orlowska-Kowalska
This short article constitutes an introductory part of the Special Section (SS) on State and Parameter Estimation Methods in Sensorless Drives. In the current issue of the journal, the first part of this section is published. Accepted articles are focussed mainly on estimation of the state variables and parameters for vector-controlled induction motor (IM) drives, using different concepts, such as different types of Kalman filters (KFs) and model reference adaptive systems (MRASs). The KF was also proposed for brushless DC motor (BLDC). Also, neural networks (NNs) have been proposed for mechanical state variables’ estimation of the drive system with elastic couplings.
Mariusz Malinowski, Emil Levi and Teresa Orlowska-Kowalska
This article constitutes an introductory part of the special section on Intelligent Fault Monitoring and Fault-Tolerant Control in Power Electronics, Drives and Renewable Energy Systems. In the current issue of the journal, the first part of this section is published. Accepted articles are focussed mainly on the sensor-fault diagnosis methods for T-type inverter-fed dual-three phase PMSM drives, partial demagnetization, faults of the permanent magnet synchronous generator (PMSG) and online open phase fault detection (FD) in the sensorless five-phase induction motor drive implemented with an inverter output LC filter and third harmonic injection. Also, neural networks (NN) application in the detection of stator and rotor electrical faults of induction motors has been proposed in one of the papers, and the observer-based FD concept for unknown systems using input–output measurements was applied to a brushless direct current motor drive with unknown parameters.