Wilson, V.Latha, P.G.Jose, N.Bhaktha, S.2026-02-032025International Journal of Power Electronics, 2025, 21, 5, pp. 471-4961756638Xhttps://doi.org/10.1504/IJPELEC.2025.148279https://idr.nitk.ac.in/handle/123456789/20637Switched reluctance motors (SRMs) have grown in popularity in a variety of industrial applications due to their inherent benefits such as high fault-tolerance, simplicity, affordability, and rare-earth free nature. However, the generation of undesirable vibrations due to radial force variations remains a significant challenge. Two stage commutation based on active vibration cancellation (AVC) is an effective method to reduce these vibrations. The focus of this paper is to address the major limitation with two stage commutation, namely the extended tail current causing increased copper loss. This is accomplished with optimal commutation parameters employing particle swarm optimisation (PSO) method. A MATLAB/Simulink model of SRM with vibration signal is developed and is used for demonstrating vibration cancellation. An intelligent control is also implemented which can track the dynamic changes in speed-load conditions. This paper showcases that this approach is an effective solution to reduce the vibrations issues in SRM, thereby improving the overall performance of the motor for industrial applications. © © 2025 Inderscience Enterprises Ltd.Electric commutationFault toleranceIntelligent controlMATLABReluctance motorsVentilation exhaustsActive vibration cancellationANNNeural-networksParticle swarmParticle swarm optimizationSwarm optimizationSwitched Reluctance Motor - SRMTwo stage commutationNeural networksParticle swarm optimization (PSO)