Performance Analysis of Position Estimation in a Quarter-Car Suspension System Using Kalman-Bucy as a State Observer - Dian Mursyitah; Ahmad Faizal; Putut Son Maria; Hilman Zarory; Alpin Adriansyah (Universitas Muhammadiyah Malang, 2026)
This study explores the implementation of the Kalman-Bucy observer for state estimation in a quarter-car suspension system operating under various real-world conditions. The research focuses on evaluating the observer’s performance in the presence of road surface disturbances, such as speed bumps, humps, and potholes, combined with stochastic noise and parameter variations. To test its robustness, the system is subjected to Gaussian white noise with an intensity of 10% in both the process and measurement signals. A sensitivity analysis is also carried out by varying the vehicle mass between 400 kilograms under unloaded conditions and 600 kilograms when fully loaded, thereby simulating different passenger and cargo scenarios. Simulation results demonstrate that the Kalman-Bucy observer consistently provides accurate and stable estimations of vehicle position, even in noisy and dynamically changing environments. The observer achieves a Root Mean Square Error (RMSE) of 3.3885 × 10⁻⁵ m, indicating near-perfect estimation accuracy. When integrated into a PID control framework, the proposed observer significantly improves system performance by reducing rise time from 9.76 s to 0.16 s, decreasing undershoot from −0.22 m to −0.15 m, and maintaining a similar settling time of approximately 25 s. Overall, the Kalman-Bucy observer proves to be a reliable and efficient method for state estimation and control enhancement in active suspension systems, showing strong potential for real-world automotive applications.