Neutrosophic Bitopological Modeling for Vibration Control Performance in Vehicle Suspension Systems under Uncertainty

Abstract

Vibration control is one of the most critical aspects in designing safe and comfortable 
vehicle suspension systems. Traditional methods such as PID, fuzzy logic, or adaptive 
control face limitations when dealing with uncertain or incomplete data about road 
conditions or vehicle dynamics. In this paper, we propose a novel mathematical 
framework based on generalized open sets in neutrosophic soft bitopological spaces to 
model and control suspension vibrations under uncertainty. By using two separate 
neutrosophic topologies, the system's response is evaluated from dual perspectives, 
capturing both predictable and unpredictable behaviors. Additionally, we incorporate 
Quadripartitioned Single-Valued Neutrosophic (QSVN) representations to quantify truth, 
contradiction, ignorance, and falsity of vibration states. This dual-layered structure allows 
for more precise, flexible, and intelligent decision-making for suspension control. A 
complete case study using a quarter-car model demonstrates how the proposed 
framework improves system robustness, especially in environments with noisy or 
conflicting sensor data. 

DOI: 10.5281/zenodo.16734032