Artificial neural network identification model of SRM 12-8

The proper identification model of the electrical motor very often turns out to be a key factor for the efficient solution of the control task. Artificial neural network description of some of the motor parameters significantly simplifies this identification. This paper particularly deals with identification of the most commonly used switched reluctance motor which has 12 stator poles and 8 rotor poles (SRM 12-8). The key point in this task is the artificial neural network description of the phase inductance and its derivatives in regards to the rotation angle and phase current. The advantages of this description are as follows: The description of the system changes from partial derivative system of equations into ordinary differential equation system. This fact extremely facilitates the Matlab Simulink model simulation. The neural networks easily describe the strong nonlinearities of the identification model.