Comparative evaluation of speed control techniques for switched reluctance motors in industrial applications

Abstract This paper offers a thorough summary of the comparative assessment of speed control methods for Switched Reluctance Motors (SRMs) in industrial settings. It is primarily concerned with two topics: optimization methods and PID controller applications. Studies on PID controllers have demonstrated improved speed control performance for SRMs; however, these findings frequently lack real-world validation and comparisons with other approaches. The difficulties with implementation are also covered. Fuzzy logic, evolutionary computation, particle swarm optimization, and genetic algorithms are some of the optimization approaches that have been used to enhance SRM speed control. However, there are still several issues with computational complexity, noise and volatility in parameters and real-time implementation. Numerous research assessed the ways in which different strategies and algorithms decreased torque ripples and controlled speed. However, these comparisons frequently fall short in terms of thoroughness and in-depth talks about real-world difficulties. All things considered, the analysis of the literature indicates a wide variety of approaches and methods for SRM speed control, each with advantages and disadvantages. Subsequent investigations may tackle these constraints, carry out more thorough comparative evaluations, and investigate the viability of actual application in industrial settings.