Optimal fractional controller design methodology for electric drive train

摘要

This investigation presents an optimisation-driven fractional order PID (FOPID) controller design methodology for brushless direct current (BLDC) motor speed control for electric vehicle applications. Though the introduction of fractional terms provides additional flexibility, their optimal selection is important for achieving desired performance. For this purpose, this investigation uses two evolutionary optimisation approaches-real coded genetic algorithm (RGA) and bio-geography based optimisation (BBO). In order to illustrate the improvements provided by FOPID, its performance is compared with conventional PID controller. Our results demonstrate that the FOPID controller tuned by BBO algorithm provides up to 50% improvements in transient response over the PID controller.