2002
DOI: 10.1109/tec.2002.801999
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A methodology for characterizing fault tolerant switched reluctance motors using neurogenetically derived models

Abstract: This paper examines the feasibility of using artificial neural networks (ANNs) and genetic algorithms (GAs) to develop discrete time dynamic models for fault free and faulted switchedreluctance-motor (SRM) drive systems. The results of using the ANN-GA-based (neurogenetic) model to predict the performance characteristics of prototype SRM drive motor under normal and abnormal operating conditions are presented and verified by comparison to test data.

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Cited by 44 publications
(24 citation statements)
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“…For fault-tolerant control, artificial neural network and genetic algorithm are developed [34]. The fuzzy logic control without a model is proposed in [35] to improve the performance of the SRM under fault conditions.…”
Section: Table I Comparison Of Fault-tolerant Methodsmentioning
confidence: 99%
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“…For fault-tolerant control, artificial neural network and genetic algorithm are developed [34]. The fuzzy logic control without a model is proposed in [35] to improve the performance of the SRM under fault conditions.…”
Section: Table I Comparison Of Fault-tolerant Methodsmentioning
confidence: 99%
“…A magnetic brake acts as the load with a torque of 1 Nm. The dc-link voltage is fixed to 48 V. The torque observed in the oscilloscope is obtained online by using the real-time phase currents and rotor position to look up for the torque value in a 3-D torque table that includes the T-i-θ characteristics [33], [34]. The torque data in the lookup table are measured by using a rotor-clamping device when supplying different steady currents to the motor windings in a rotor position that changes step by step.…”
Section: Simulation and Experimentsmentioning
confidence: 99%
“…In order to balance the voltage across the capacitors, it will be considered a control law associated to these capacitor voltages. This law is given by (11) and consists in the difference between the measured capacitor voltages. (11) From the analysis of the circuit and the switches states presented in Table 2, is possible to see that for the intermediate voltage +V DC /2 and positive winding current, state 1 discharges upper capacitor and state 3 discharges the lower capacitor.…”
Section: Control Of the Drive And Balance Of The DC Voltage Capacmentioning
confidence: 99%
“…The modification of the switching states of the power semiconductors are proposed in [10]. Other approaches use artificial neural networks and genetic algorithms [11], the analyses of different fault tolerant situations with traditional Proportional-Integral (PI) and Integral-Proportional (IP) regulators [12], fault detections schemes [13] or even the modification of the geometry of the system using dual-channel SRM [14]. In [15] a mutually coupled dual three-phase SRM is used and in [16]- [18] it is adopted, as fault tolerant control strategy, the modification of the control parameters and references.…”
Section: Introductionmentioning
confidence: 99%
“…In [7], the superior fault-tolerance characteristics of a four-phase 8/6 SRM under various types of motor winding faults have been proved in a working laboratory. In [8], an artificialneural-network model was developed to predict faulttolerant performance of an SRM. To enhance the faulty performance of SRMs, a model-free adaptive fuzzy controller was proposed by Mir [9].…”
Section: Introductionmentioning
confidence: 99%