OPTIMIZING FUZZY LOGIC CONTROL FOR VEHICLE PATH TRACKING WITH PARTICLE SWARM OPTIMIZATION

Abstract

This paper presents an optimal path tracking scheme for a vehicle handling dynamics model with eight degrees of freedom. A fuzzy logic controller (FLC) is incorporated to handle nonlinearities using heuristic rules. Particle Swarm Optimization (PSO) is applied to optimize the scaling factors of the FLC outputs, ensuring normalized ranges for controller inputs and outputs. The optimization achieved convergence within 154 iterations. Simulation results under ISO lane change maneuvers at 70-80 kph demonstrate that the optimized fuzzy controller significantly improves trajectory tracking performance, reducing lateral deviation and enhancing control stability compared to the baseline controller.