Enhancing ride comfort of semi-active suspension through collaboration control using dung beetle optimizer optimized Fuzzy PID controller

This research addresses the challenge of improving ride comfort and driving experience in modern vehicles by optimizing semi-active suspension control strategies. Traditional fuzzy control methods often face limitations in online real-time adjustments and parameter tuning. To overcome these constraints, the paper proposes a collaborative control strategy that integrates the Dung Beetle Optimizer (DBO), Fuzzy logic, and Proportional-Integral-Derivative (PID) control to regulate a magnetorheological (MR) damper. In this hybrid framework, the initial control parameters generated by the fuzzy controller serve as the starting values for the DBO algorithm's iterative optimization. The resulting optimal parameters are then supplied to the PID controller to adjust the actuator's magnetic field. Evaluated using a quarter-car

semi-active suspension model in MATLAB/Simulink under sinusoidal and random road disturbances, the Fuzzy-DBO-PID controller demonstrated significant improvements. Specifically, the paper reports vehicle acceleration reductions of up to 51% compared to passive suspension, and up to 32.86% compared to standard Fuzzy-PID control. While the simulation results show promising performance enhancements, real-world hardware-in-the-loop validation and physical constraints of the MR damper coil dynamics remain areas for further empirical investigation.

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