Vehicle State Estimation Usinga State Dependent Riccati Equation
IFAC PAPERSONLINE(2017)
Abstract
In this paper a Vehicle State Estimator is developed and validated on experimental data from a 2012 Toyota Prius. The estimator is capable of estimating both planar vehicle velocities and the tyre-road friction parameter. Emphasis is placed on the comparison of the commonly used Extended Kalman Filter and a novel application of the State Dependent Riccati Equation technique. The State Dependent Riccati based estimator relies on a factorization compared to linearization in the case of the Extended Kalman Filter. This factorization is non-unique, therefore the construction of this factorization, is also presented. A comparison is for both estimators is presented for experimental data. For estimation of the tyre-road friction parameter, simulations are used, due to absence of a reference value in the experimental set-up. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
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Key words
State Estimation, Riccati equations, Extended Kalman filters, Parameter Estimation, Vehicle Dynamics, Vehicle Control
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