Vehicle state estimation using a state dependent Riccati equation

Robbin van Hoek, Mohsen Alirezaei, Antoine Schmeitz, Henk Nijmeijer

Research output: Contribution to journalConference articlepeer-review

6 Citations (Scopus)
4 Downloads (Pure)


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.

Original languageEnglish
Pages (from-to)3388-3393
Number of pages6
Issue number1
Publication statusPublished - 1 Jul 2017


  • Extended Kalman filters
  • Parameter Estimation
  • Riccati equations
  • State Estimation
  • Vehicle Control
  • Vehicle Dynamics


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