Compensation for the iron loss effect in EKF-based speed estimation of vector controlled induction motors

In vector controlled induction motor drives, the instantaneous rotor speed is measured using whether sensors or estimators. Since the basic Kalman filter is a state observer, its use in vector controlled schemes has received much attention. However, these schemes are based on the assumption that the existence of iron loss in an induction motor may be neglected. The paper shows the effect of iron loss on the extended Kalman filter performance that is designed on the basis if the ironless induction machine model. Simulation results are carried out to demonstrate this effect as well as the effectiveness of the suggested approach to minimise the speed estimation error without modifying the observer algorith

Minimum action time of a robust fuzzy speed controller for induction machine drive

In this paper, we propose a procedure to design an optimal fuzzy controller for indirect field oriented controlled induction machine drives. This controller has best possible performances with a minimum action time possible in a practical implementation. First, we design a fuzzy PI controller having the maximum of fuzzy sets (7 input/output membership functions), which show better static and dynamic performances. This controller is specific to speed close loop of an indirect field oriented induction machine drive. Then, in order to minimize its composition the ANFIS (Adaptive Network-Based Fuzzy Inference System) structure is applied to perform a structural and parametric optimization of this controller. We propose also, a procedure to reproduce the input/output mapping of this controller with an approximation using artificial neural networks (ANN

ANN based double stator asynchronous machine diagnosis taking torque change into account

In this work the strategy of the artificial intelligence (neural networks) is used to detect and localize the defects of the double stator asynchronous machine. In fact, several neural networks have been applied to the detection of defects. Then, we used a selector which allows activating only one network at a time. In this case, the selected network detects only defects corresponding to the torque developed by asynchronous machine. Finally, the simulation results were presented to show the effectiveness of artificial neural networks for automatic fault diagnosi

Extended-Kalman-filter based sensorless speed vector control of induction motor taking iron loss into account

In vector controlled induction motor drives, the instantaneous rotor speed is measured using whether sensors or estimators. Since the basic Kaiman filter is a state observer, its use in vector controlled schemes has received much attention. However, these schemes are based on the assumption that the existence of iron loss in an induction motor may be neglected. The paper shows the effect of iron loss on the extended Kaiman filter performance that is designed on the basis if the ironless induction machine model. Original simulation results are carried out to demonstrate this effect as well as the effectiveness of the suggested approach to minimise the speed estimation error without modifying the observer algorith

Choice of input data type of artificial neural network to detect faults in alternative current systems

This paper present a study on different input data types of ANN used to detect faults such as overvoltage in AC systems (AC network , induction motor). The input data of ANN are AC voltage and current. In no fault condition, voltage and current are sinusoidal. The input data of the ANN may be the instantaneous values of voltage and current, their RMS values or their average values after been rectified. In this paper we presented different characteristics of each one of these data. A digital software C++ simulation program was developed and simulation results were presente

Use of asymmetrical currents waveforms to detect and localize open switch faults for two level voltage source inverter three-phase shunt active power filter

This paper proposes an open switch faults detection and localization algorithm for shunt three phase active filter topology. It mainly details converter configuration and examines a simple and reliable optimized fault diagnosis method. The converter topology is based on classical three-leg active power filter topology. New fault diagnosis method is proposed, based on classical currents measurements. It includes combinatory logic to analyze and validate error signals. Hysteresis control is applied before and after fault detection, which avoids any controller reconfiguration. Simulation results obtained with Matlab/Simulink/Plecs tools prove the effectiveness of this method