Optimization methods in fractional order control of electric drives: A comparative study

Abstract

This paper presents a comparative study on the optimization methods in fractional PID controller design for induction motor. Choosing the best optimization algorithm for tuning fractional order controllers is crucial in order obtain best system response. In this study genetic algorithm, local search, nonlinear sequential quadratic programming, and particle swarm optimization algorithms are used to tune a fractional PI controller for induction motors. A model of a real motor is used to design and test the controllers. The resulted fractional controllers are approximated using refined Oustaloup's recursive filter in order to be implemented using digital controllers. The controllers' speed tracking performance is tested in simulation and a comparative analysis has been conducted.