Resilient Corner-Based Vehicle Velocity Estimation

© 2017 IEEE. Pirani, M., Hashemi, E., Khajepour, A., Fidan, B., Kasaiezadeh, A., Chen, S.-K., & Litkouhi, B. (2017). Resilient Corner-Based Vehicle Velocity Estimation. IEEE Transactions on Control Systems Technology, 1–11. https://doi.org/10.1109/TCST.2017.2669157This paper presents longitudinal and lateral velocity estimators by considering the effect of the suspension compliance (SC) at each corner (tire) for ground vehicles. The estimators are developed to be resilient to sensor measurement inaccuracies, model and tire parameter uncertainties, switchings in observer gains, and measurement failures. More particularly, the stability of the observer is investigated, and its robustness to road condition uncertainties and sensor noises is analyzed. The sensitivity of the observers' stability and performance to the model parameter changes is discussed. Moreover, the stability of the velocity observers for two cases of arbitrary and stochastic switching gains is investigated. The stochastic stability of the observer in the presence of faulty measurements is also studied, and it is shown that if the probability of a faulty measurement occurring is less than a certain threshold, the observer error dynamics will remain stochastically stable. The performance of the observer and the effect of the SC are validated via several road experiments.Automotive Partnership Canada || Ontario Research Fund || General Motors Co. [grant numbers APCPJ 395996-09 and ORF-RE-04-039

A DVS-MHE Approach to Vehicle Side-Slip Angle Estimation

A study on the application of a direct virtual sensor-moving horizon estimator (DVS-MHE) to the problem of vehicle side-slip angle estimation is carried out. In particular, it is shown that a stable MHE can be represented as nonlinear finite impulse response (NFIR) filter. Then, in order to allow online implementation and guaranteed estimation accuracy, an optimal NFIR filter is derived directly from the data by means of a DVS approach. Comparisons between the standard model-based MHE approach and the DVS approach are carried out using a detailed vehicle mode