Robust fault-tolerant control strategy for active suspension based on disturbance observer

Abstract

High-performance automotive active suspension systems, with real-time dynamic regulation capabilities for ride and handling enhancement, are drawing growing interest from both academia and industry. In order to solve the problems of inaccurate estimation of active suspension disturbance and difficulty in handling uncertainty with fault-tolerant control, this paper proposes a robust fault-tolerant control strategy for active suspension based on disturbance observer. A high-fidelity half-car suspension model is firstly established, incorporating both vertical and pitch dynamics with actuator fault characteristics. Secondly, in order to solve the problem of system uncertainty, an improved disturbance observer based on Kalman filter is further proposed, which realizes the accurate estimation of unmodeled dynamics and external interference by introducing disturbance estimators. Furthermore, based on the state estimation residuals, a multi-criterion fault detection and diagnosis unit is designed, and an active fault-tolerant control strategy with strong robustness to model parameter changes is proposed. The results demonstrate that the proposed fault-tolerant controller effectively compensates for actuator failures and preserves system stability under parameter and random disturbances. The proposed controller outperforms the control group, reducing the root mean square of vehicle body acceleration by 2.3% and the root mean square of tire dynamic stroke by 42.1%. Meanwhile, the enhanced Kalman filter embedded with a disturbance observer reduces the mean square error of state estimation by 5.12% and 4.81% respectively compared with the standard Kalman filter, yielding remarkable improvement in estimation accuracy.