Abstract
This article presents possible benefits of using derivative-free filter to estimate vehicle dynamics states based on measured signals where the complexity of nonlinear dynamics limits the use of Extended Kalman Filter commonly used for nonlinear filtering. The filtration process was applied to real data obtained from testing manoeuvre. Bicycle model of a vehicle was used for state description and lateral dynamics investigation. Filter implementation in Matlab-Simulink software environment was used for analysis and comparison with earlier results published in [2].
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Porteš, P., Laurinec, M., Blat’ák, O. (2010). Discrete-Difference Filter in Vehicle Dynamics Analysis. In: Brezina, T., Jablonski, R. (eds) Recent Advances in Mechatronics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05022-0_4
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DOI: https://doi.org/10.1007/978-3-642-05022-0_4
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