Estimation of airship states and model uncertainties using nonlinear estimators

  • Muhammad Wasim Department of Aeronautics and Astronautics Engineering, Institute of Space Technology, Islamabad Pakistan
  • Ahsan Ali Department of Electrical Engineering, University of Engineering and Technology, Taxila Pakistan
  • Muhammad Mateen Afzal Awan Department of Electrical Engineering, University of Management and Technology, Sialkot Pakistan
  • Inam ul Hasan Shaikh Department of Electrical Engineering, University of Engineering and Technology, Taxila Pakistan

Abstract

This Airships are lighter than air vehicles and due to their growing number of applications, they are becoming attractive for the research community. Most of the applications require an airship autonomous flight controller which needs an accurate model and state information. Usually, airship states are affected by noise and states information can be lost in the case of sensor's faults, while airship model is affected by model inaccuracies and model uncertainties. This paper presents the application of nonlinear and Bayesian estimators for estimating the states and model uncertainties of neutrally buoyant airship. It is considered that minimum sensor measurements are available, and data is corrupted with process and measurement noise. A novel lumped model uncertainty estimation approach is formulated where airship model is augmented with six extra state variables capturing the model uncertainty of the airship. The designed estimator estimates the airship model uncertainty along with its states. Nonlinear estimators, Extended Kalman Filter and Unscented Kalman Filter are designed for estimating airship attitude, linear velocities, angular velocities and model uncertainties. While Particle filter is designed for the estimation of airship attitude, linear velocities and angular velocities. Simulations have been performed using nonlinear 6-DOF simulation model of experimental airship for assessing the estimator performances. 1−𝜎 uncertainty bound and error analysis have been performed for the validation. A comparative study of the estimator's performances is also carried out.

Published
Jan 1, 2024
How to Cite
WASIM, Muhammad et al. Estimation of airship states and model uncertainties using nonlinear estimators. Mehran University Research Journal of Engineering and Technology, [S.l.], v. 43, n. 1, p. 55-69, jan. 2024. ISSN 2413-7219. Available at: <https://publications.muet.edu.pk/index.php/muetrj/article/view/1613>. Date accessed: 27 feb. 2024. doi: http://dx.doi.org/10.22581/muet1982.2401.1613.
This is an open Access Article published by Mehran University of Engineering and Technolgy, Jamshoro under CCBY 4.0 International License