OPTIMIZING FRACTIONAL ORDER PID CONTROLLER FOR DC MOTOR SPEED CONTROL USING ARTIFICIAL HUMMINGBIRD ALGORITHM
Abstract
This study implements the artificial hummingbird algorithm (AHA) to tune the FOPID controller optimally for DC motor speed control. The AHA algorithm is a straightforward and efficient method that mathematically simulates the foraging strategies of hummingbirds. It has been specifically designed to tackle a wide range of optimisation challenges. For a fair comparison, the proposed AHA-FOPID controller is tuned using the ITAE objective function and evaluated alongside the controllers optimized through GWO, PSO, and DE in the previous researches. Additionally, transient response analysis and load disturbance analysis are conducted. The suggested controller exhibits exceptional transient performance, as seen by a settling time of 0.0329 seconds, a rising time of 0.0208 seconds, and no overshoot. The simulation findings are encouraging and confirm the efficacy of the proposed technique. Ultimately, a statistical analysis is conducted to confirm the superiority of the proposed method.
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