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January 18, 2026International Journal of Robust and Nonlinear ControlOpen Access

Comparative Analysis of the Performances of a Nonlinear Observer and Nonlinear Kalman Filters in the Presence of Non‐Gaussian Disturbances

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Authors

HMHamidreza MovahediAZA. ZemoucheRRRajesh Rajamani

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Overview

Comparative analysis shows nonlinear observer performs better than Kalman filters in noisy systems, highlighting effectiveness.

Key Points

  • This research aims to analyze the performance of a nonlinear observer against nonlinear Kalman filters under non-Gaussian disturbances.
  • Developed a nonlinear observer using Lyapunov analysis for state estimation.
  • Applied the observer to different systems with varying disturbance levels.
  • Compared performance against extended Kalman filter (EKF) and unscented Kalman filter (UKF) across three applications.
  • In Gaussian noise scenarios, UKF and nonlinear observer showed similar performance, both superior to EKF.
  • In cases of non-Gaussian disturbances, the nonlinear observer significantly outperformed both UKF and EKF.
  • Experimental results across various covariance choices confirmed the robustness of the nonlinear observer.

Cite This Study

Movahedi et al. (2026) studied this question.

synapsesocial.com/papers/696c789ceb60fb80d1396cb3https://doi.org/10.1002/rnc.70386
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