Modeling and Simulation of a Current Controlled Multimodal Neural Network Controller (CCMNN) Based Switched Reluctance Motor

In this work, Current Controlled Multimodal Neural network controller (CCMNN) based integral switching for 3 phase 6/4 poles SRM implemented. This work is aimed to employ fast and efficient ripple free neural network algorithm that improve the efficiency of SRM drive from vibrations and acoustic noise. The researchers mainly focus on the design and development of high-performance controllers for SRM drives system. To integrate the Rotor current characteristics, SRM drive Current Controlled Multimodal Neural network controller (CCMNN) is derived. Here the current sharing coordinate function approach is used where each phase current separated and converted into proposed flux characteristics of the SRM. The proposed Current Controlled Multimodal Neural network controller (CCMNN) is implemented here which is used to improve the SRM modeling parameters of torque, speed and current response. The simulation results show that Current Controlled Multimodal Neural network controller (CCMNN) proves enhanced responses of transient and steady-state at different levels of speed and torque.