Optimal control of variable reluctance motor by neural network

This paper describes the problem of designing the real time optimal efficiency control of a variable reluctance motor (VRM) operating at the desired torque speed. An application of a neural network is proposed to perform optimization of the motor excitation such that the drive efficiency is maximized subject to the torque speed requirements. The most interesting feature of the proposed neuromorphic controller is the possibility of adapting computation of the optimal control in real-time for the drive system.