Vehicle state estimation based on minimum model error criterion combining with extended Kalman filter

DOI10.1016/j.jfranklin.2016.01.005zbMath1395.93518OpenAlexW2293058369MaRDI QIDQ1660971

Fengchun Sun, Hongwen He, Wei Liu

Publication date: 16 August 2018

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2016.01.005

zbMATH Keywords

extended Kalman filtervehicle state estimationminimum model error

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Nonlinear systems in control theory (93C10) Application models in control theory (93C95) Estimation and detection in stochastic control theory (93E10) Control/observation systems governed by ordinary differential equations (93C15)

Related Items (4)

Nonlinear stochastic position and attitude filter on the special Euclidean group 3 ⋮ Desensitized cubature Kalman filter with uncertain parameters ⋮ Adaptive filtering-based recursive identification for time-varying Wiener output-error systems with unknown noise statistics ⋮ Running states estimation of autonomous four-wheel independent drive electric vehicle by virtual longitudinal force sensors

Uses Software

• Carsim

Cites Work

• Vehicle velocity estimation using nonlinear observers
• Minimum model error estimation for poorly modeled dynamic systems
• Minimum Model Error Approach for Attitude Estimation
• A new method for the nonlinear transformation of means and covariances in filters and estimators

This page was built for publication: Vehicle state estimation based on minimum model error criterion combining with extended Kalman filter