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|Title:||Application of spatial iterative learning control for direct torque control of switched reluctance motor drive||Authors:||Sahoo, S.K.
|Keywords:||Direct torque control
Iterative learning control
Switched reluctance motor
Torque ripple minimization
|Issue Date:||2007||Citation:||Sahoo, S.K.,Panda, S.K.,Xu, J.X. (2007). Application of spatial iterative learning control for direct torque control of switched reluctance motor drive. 2007 IEEE Power Engineering Society General Meeting, PES : -. ScholarBank@NUS Repository. https://doi.org/10.1109/PES.2007.385538||Abstract:||In this paper, a novel direct torque controller for switched reluctance motor (SRM) is proposed using spatial iterative learning control (ILC). SRM magnetization characteristics are highly non-linear, and torque is a complex and coupled function of phase current and rotor position. Direct torque control (DTC) scheme avoids the complexity of torque-to-current conversion as required in indirect torque control scheme. Traditional DTC scheme uses a hysteresis controller and leads to large amount of torque ripples when implemented using a digital controller. Advanced non-linear control methods can be used to improve the performance of DTC in SRM. However, such methods are often too complex for real-time implementation or require an accurate model of SRM magnetization characteristics. As shown here, ILC only uses a linearized magnetization characteristics and a simple learning law to obtain the desired control signal. An ILC based DTC scheme for SRM torque control for constant motor torque, has been developed and experimentally verified on a 1-hp, 4-phase SRM. Experimental results show the effectiveness of the proposed scheme in terms of average torque control and ripple minimization. © 2007 IEEE.||Source Title:||2007 IEEE Power Engineering Society General Meeting, PES||URI:||http://scholarbank.nus.edu.sg/handle/10635/69434||ISBN:||1424412986||DOI:||10.1109/PES.2007.385538|
|Appears in Collections:||Staff Publications|
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