Aquila Optimizer-Based Filtered PID Controller Design for A Spark Ignition Engine Speed Control

This paper presents a novel approach for optimizing the speed control of a four-cylinder spark ignition engine (SIE) using a filtered proportional-integral-derivative (PID) controller tuned by the aquila optimizer (AO). SIEs require precise speed control to enhance performance, fuel efficiency, and emission regulation. Traditional PID controllers, while widely employed, face significant challenges in parameter tuning due to nonlinear engine behavior. The AO, inspired by the hunting techniques of the aquila bird, effectively optimizes the controller’s parameters. Comparative simulations between AO, differential evolution (DE), grey wolf optimizer (GWO), and Simulink PID tuner show that AO achieves better performance in terms of minimizing the integral of time-weighted absolute error (ITAE). The AO-based controller delivers faster settling times and reduced overshoot, indicating its superior capability in maintaining engine stability during speed transitions.