Flood Algorithm-Tuned PID-F Controller with a Modified Objective Function for Robust and Noise-resilient Speed Control of Nonlinear SparkIgnition Engines

This study presents a novel control strategy for the regulation of engine speed in nonlinear four-cylinder spark ignition (SI) engines by integrating a proportional-integral-derivative controller with a filter (PID-F) tuned using the flood algorithm (FLA). The approach leverages the dual-phase exploration and exploitation mechanism of FLA to determine optimal controller parameters efficiently, addressing the nonlinear and time-varying behavior of SI engines. A modified objective function is formulated to penalize overshoot and cumulative tracking error simultaneously, ensuring rapid transient response and precise steady-state accuracy. The proposed control framework is modeled and validated in MATLAB/Simulink and benchmarked against existing tuning techniques, including the Simulink PID tuner and selected metaheuristic optimizers such as the whale optimization algorithm, sinh-cosh optimizer, and cuckoo search. Comparative analyses demonstrate the superiority of the FLA-optimized PID-F controller in achieving stable, robust, and noise-resilient speed regulation under varying load and disturbance conditions. The findings establish the FLA as an efficient and scalable optimization tool for real-time controller tuning in automotive applications, contributing to a practical and computationally efficient solution for advanced engine control systems.