A random-walk-aided RIME optimizer for optimizing the PI controller of a four-cylinder spark-ignition engine

Abstract

The accurate control of engine speed in four-cylinder spark ignition engines is critical for optimizing performance, minimizing fuel consumption, and reducing emissions. This paper presents a novel approach to tuning a proportional-integral (PI) controller using the random walk aided RIME (RW-RIME) optimizer, a novel metaheuristic algorithm designed to enhance the search process by incorporating random walk (RW) mechanisms into the RIME framework. The engine speed control problem is modeled as a nonlinear system, and the proposed RW-RIME algorithm is used to optimize the PI controller’s parameters. The efficacy of the approach is demonstrated through comprehensive simulation experiments, where the performance of RW-RIME is compared against other optimization techniques, including the original RIME algorithm, particle swarm optimization, genetic algorithm, and Simulink PID tuner. Results indicate that the RW-RIME-based PI controller achieves faster convergence, reduced overshoot, and shorter settling times compared to competing methods, making it a robust and efficient solution for nonlinear systems like spark ignition engines.