Robust Estimation for Nonlinear Continuous-Discrete Systems With Missing Outputs: Application to Automatic Train Control

doi:10.1109/TCST.2021.3101737

Robust Estimation for Nonlinear Continuous-Discrete Systems With Missing Outputs: Application to Automatic Train Control

2022-05-01

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DOI：10.1109/TCST.2021.3101737

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Abstract

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This brief is about robust estimation for a sampled output system with continuous dynamics using unknown input observers (UIOs). A novel worst case estimation error bound is developed using a particular form of Gronwall inequality. The motivation is to assess the accuracy of the estimator in real-world conditions, considering slow sensor sampling times and possible corruption of the measurements due to faults. The theoretical results are applied for robust velocity estimation of a braking train when wheel jamming faults affect odometric sensors. Simulations and experimental data analysis are used to evaluate the proposed approach.

Keywords:

Observers

Convergence

Time measurement

Measurement uncertainty

Linear matrix inequalities

Estimation error

Uncertainty

Bounded error

continuous-discrete systems

Gronwall inequality

linear matrix inequalities

nonlinear systems

unknown input observer (UIO)

Robust Estimation for Nonlinear Continuous-Discrete Systems With Missing Outputs: Application to Automatic Train Control

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