A Metaheuristic Approach for Optimal Tuning of PIDD^α Controller for AVR Performance Improvement

This paper presents an effective controller design technique for the automatic voltage regulator system where an additional fractional-order derivative term is incorporated along with the standard PID controller structure, resulting in the PIDD <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\alpha$</tex> structure. The proposed controller is tuned using a recently reported metaheuristic optimizer, namely the Manta Ray Foraging Optimization Algorithm (MRFOA). Average per-formance for the proposed approach is studied by considering various performance metrics. Comparison with those of the recently reported controllers of different types demonstrates significant improvement in rise time (0.0682 s) and settling time (0.1044 s) along with competitive peak overshoot characteristics (0.75%) for the proposed MRFOA-PIDD<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">${}^\alpha$</tex> controller.