Introduction to the Special Section on State and Parameter Estimation Methods for Sensorless Drives

This short article constitutes an introductory part the Special Section 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 focused mainly on the state variables and parameters estimation for vector controlled induction motor drives, using different concepts, like different types of Kalman Filters (KFs) or Model Reference Adaptive Systems (MRASs). The Kalman filter was also proposed for Brushless DC Motor (BLDC). Also neural networks (NN) have been proposed for mechanical state variables estimation of the drive system with elastic couplings.

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Real-time Neural Sliding Mode Linearization Control for a Doubly Fed Induction Generator under Disturbances

Design and Simulation of Direct and Indirect Back EMF Sliding Mode Observer for Sensorless Control of PMSM

Simple Technique of Initial Speed Identification for Speed-Sensorless Predictive Controlled Induction Motor Drive

Simulation Analysis of Extended Kalman Filter Applied for Estimating Position and Speed of a Brushless DC Motor

Dynamic Performance of Estimator-based Speed Sensorless Control of Induction Machines Using Extended and Unscented Kalman Filters

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