ANFIS based speed and current control with torque ripple minimization using hybrid SSD-SFO for switched reluctance motor

Abstract SRM (Switched Reluctance motor) is gaining much interest in industries due to its straightforward structure, low-cost manufacturability and dependability which makes it better than other electric machines. SRM drive is the most appropriate for variable speed tasks. Additionally, the performance of the current and speed control for the SRM driver framework could be negatively influenced by noise, disturbances, and inactivity of load torque. To solve this difficulty, this paper develop an ANFIS based Speed and Current control with Torque Ripple Minimization using Hybrid SSD-SFO for SRM. The main goal of this work is to obtain preferred current and speed performance of SRM with minimum torque ripple. For concurrent regulator of the speed and current, an ANFIS (Adaptive Neuro-Fuzzy Inference System) structure is employed which includes two controlling loops. The inside loop is regulated for control of current and the outside loop is regulated for control of speed even with perfect choice of switching angles. The dynamic conduct of SRM is studied to restrict the current and speed that reduces the ripple of torque. Hybrid SSD-SFO (social ski-diver based sunflower optimization) procedure is employed to achieve the parameter values of current and speed control of SRM. The proposed scheme is accomplished by MATLAB/ Simulink environment. The results show that the hybrid SSD-SFO scheme given the better performance compared to the SSD and SFO algorithm.