☆ 4.5 Article

UKF Estimation Method of Centroid Slip Angle for Vehicle Stability Control

INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS (2023)

Sliding mode adaptive control for ship path following with sideslip angle observer

Hugan Zhang et al.

Summary: An adaptive sliding mode control algorithm based on radial basis function neural networks(RBF-NNs) is proposed to solve the problems of external disturbances, internal model uncertainty and sideslip angle unknown in the process of underactuated ship path following. The RBF-NNs are used to estimate the sideslip angle, while the linear extended state observer (LESO) is introduced to estimate the total disturbances. This approach provides a potential reference for underactuated ship path following with unknown sideslip and disturbances.

OCEAN ENGINEERING (2022)

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Article Engineering, Electrical & Electronic

Vehicle Sideslip Angle Estimation Based on Interacting Multiple Model Kalman Filter Using Low-Cost Sensor Fusion

Giseo Park

Summary: This study proposes a new method for estimating the vehicle sideslip angle using in-vehicle sensors and low-cost standalone GPS. The method combines two extended Kalman filters to estimate unmeasurable vehicle states, and the observability of the algorithm is checked using observability functions. The algorithm is validated through experiments and compared to other methods, demonstrating its high optimality and accuracy in estimating the vehicle sideslip angle.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2022)

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Article Engineering, Mechanical