Coefficient determination of adaptive feedback linearization method, using multi-objective optimization based on genetic algorithm for position control of switched reluctance motors

This paper presents a new method for coefficient determination of feedback linearization control method for position control of switched reluctance motors. Feed back linearization method is unstable against uncertainties of rotor inertia and stator resistance, this disadvantage makes us to design a method that is robust against those mentioned uncertainties, in this paper by adding a torque term to the motor dynamical equation, we have made the controlling method, robust against uncertainties of rotor inertia and stator resistance. The main problem in adaptive feed back linearization method is determination of its feed back coefficients, multi-objective optimization based on genetic algorithm is proposed as an stochastic method to determine the coefficients. The major gain of our proposed method compared to those reported so far, is that, it needs less time to converge and also less speed rise time. Because of the significance of determining the coefficients precisely, the proposed method can be used in these applications, the simulation results have been compared with trial and error method and show the benefits of the proposed method.