Fuzzy PID control of two-axle electronic differential system

In this thesis, classical PID and fuzzy logic-based PID control strategies were investigated for the control of electronic differential systems used in multi-axle steered electric vehicles. Vehicle models with 4x4 and 6x6 configurations were developed, and wheel steering angles were calculated based on the Ackermann steering geometry. The developed mathematical models were simulated in the MATLAB/Simulink environment, and the performance of the controllers was analyzed. According to the simulation results, the fuzzy PID controller achieved approximately 98.79% shorter settling time, 57.3% lower maximum overshoot, and about 39.37% lower Mean Absolute Error (MAE) compared to the classical PID controller, resulting in improved system stability. In this context, the developed control system is suitable for tactical unmanned ground vehicles that require high maneuverability. The findings demonstrate that fuzzy logic offers a significant advantage in the control of multi-axle steered electronic differential systems, contributing to the existing literature in this field.