Parameter Identification and Control of DC Motor using Firefly Algorithm

Abstract

In this work we have applied the firefly algorithm (FFA) for some non linear benchmark functions to highlight the efficacy of the algorithm. There are two commonly used approaches to relate the output with its input: transfer function, state space representation. Then, a dc motor modeled using armature resistance control and field control method by transfer function, state space representation approaches. We have used the transfer function approach to identify the parameters of armature controlled dc shunt motor viz. armature resistance, armature inductance, moment of inertia, viscous friction, back emf/ torque constant by proposed algorithm. Then, we validate our result from the experimental approach. Thereafter, we have controlled the dc motor using PI controller because of its better responsiveness and improvement of the steady state response. There is a need to control its parameters according to our requirement. There are different classical tuning methods to tune the parameters of the controller viz. Ziegler-Nichols, Tyreus- Luyben, Astrom-Hagglund etc. Then, we have applied proposed algorithm to tune the parameters of the controller and compared its performance with the classical tuning methods.