Performance Evaluation of Ant Lion Optimizer–Based PID Controller for Speed Control of PMSM

Abstract

Abstract A Permanent Magnet Synchronous Motor (PMSM) is dominantly used in applications like electric vehicles, rolling mills, and servo drives. In order to efficiently run PMSM in drive applications, it needs a control strategy. A Proportional-Integral-Derivative (PID) controller is widely used in control loops to perform the automation process. The PID parameters can be tuned using optimization techniques to get a better performance. Upon advancement in computing techniques, it has become simpler to employ complex algorithms for control applications. One such stochastic optimization algorithm is Ant Lion Optimization (ALO). Its performance has been proven against a few other established algorithms of the same kind for a particular set of test functions. In this article, ALO is used to tune a PID controller for speed control of PMSM. The effectiveness of the optimizer is verified with simulation and experimental results.