Estimation of Airship Aerodynamic Forces and Torques Using Extended Kalman Filter
An airship is a lighter than air, aerial vehicle whose model is based on dynamic, aerodynamic, aerostatic and propulsion forces and torques. Apart from other, aerodynamic forces and toques are difficult to measure. In this work, an estimation scheme for aerodynamic forces and torques based on the Ex...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9057656/ |
| _version_ | 1818664557625737216 |
|---|---|
| author | Muhammad Wasim Ahsan Ali |
| author_facet | Muhammad Wasim Ahsan Ali |
| author_sort | Muhammad Wasim |
| collection | DOAJ |
| description | An airship is a lighter than air, aerial vehicle whose model is based on dynamic, aerodynamic, aerostatic and propulsion forces and torques. Apart from other, aerodynamic forces and toques are difficult to measure. In this work, an estimation scheme for aerodynamic forces and torques based on the Extended Kalman Filter (EKF) is presented. It is assumed that the airship attitude and position estimates are available. EKF estimates the airship body axes linear and angular velocities and aerodynamic forces and torques. As the method measures a complete aerodynamic model instead of measuring its individual parameters by utilizing minimum auxiliary state variables, it is computationally non-intensive and can provide online aerodynamic model information that can be used in controller implementation in a real-time environment. Nonlinear simulation environment is developed for the experimental airship and EKF performance is evaluated. For validating the estimator's performance, 3-σ uncertainty bounds and error analysis, estimator convergence analysis and it's closed-loop simulations with Sliding Mode Controller have been performed. The simulation results show that EKF successfully estimates the airship states and aerodynamic forces and torques with minimum estimation error enhancing the model-based nonlinear controller performance. |
| first_indexed | 2024-12-17T05:34:38Z |
| format | Article |
| id | doaj.art-a17071bf536a4170a186717ce1767b0a |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-17T05:34:38Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-a17071bf536a4170a186717ce1767b0a2022-12-21T22:01:39ZengIEEEIEEE Access2169-35362020-01-018702047021510.1109/ACCESS.2020.29861909057656Estimation of Airship Aerodynamic Forces and Torques Using Extended Kalman FilterMuhammad Wasim0https://orcid.org/0000-0002-5547-8234Ahsan Ali1Department of Electrical Engineering, University of Engineering and Technology, Taxila, PakistanDepartment of Electrical Engineering, University of Engineering and Technology, Taxila, PakistanAn airship is a lighter than air, aerial vehicle whose model is based on dynamic, aerodynamic, aerostatic and propulsion forces and torques. Apart from other, aerodynamic forces and toques are difficult to measure. In this work, an estimation scheme for aerodynamic forces and torques based on the Extended Kalman Filter (EKF) is presented. It is assumed that the airship attitude and position estimates are available. EKF estimates the airship body axes linear and angular velocities and aerodynamic forces and torques. As the method measures a complete aerodynamic model instead of measuring its individual parameters by utilizing minimum auxiliary state variables, it is computationally non-intensive and can provide online aerodynamic model information that can be used in controller implementation in a real-time environment. Nonlinear simulation environment is developed for the experimental airship and EKF performance is evaluated. For validating the estimator's performance, 3-σ uncertainty bounds and error analysis, estimator convergence analysis and it's closed-loop simulations with Sliding Mode Controller have been performed. The simulation results show that EKF successfully estimates the airship states and aerodynamic forces and torques with minimum estimation error enhancing the model-based nonlinear controller performance.https://ieeexplore.ieee.org/document/9057656/Airshipextended Kalman filteraerodynamic model estimationstate estimation |
| spellingShingle | Muhammad Wasim Ahsan Ali Estimation of Airship Aerodynamic Forces and Torques Using Extended Kalman Filter IEEE Access Airship extended Kalman filter aerodynamic model estimation state estimation |
| title | Estimation of Airship Aerodynamic Forces and Torques Using Extended Kalman Filter |
| title_full | Estimation of Airship Aerodynamic Forces and Torques Using Extended Kalman Filter |
| title_fullStr | Estimation of Airship Aerodynamic Forces and Torques Using Extended Kalman Filter |
| title_full_unstemmed | Estimation of Airship Aerodynamic Forces and Torques Using Extended Kalman Filter |
| title_short | Estimation of Airship Aerodynamic Forces and Torques Using Extended Kalman Filter |
| title_sort | estimation of airship aerodynamic forces and torques using extended kalman filter |
| topic | Airship extended Kalman filter aerodynamic model estimation state estimation |
| url | https://ieeexplore.ieee.org/document/9057656/ |
| work_keys_str_mv | AT muhammadwasim estimationofairshipaerodynamicforcesandtorquesusingextendedkalmanfilter AT ahsanali estimationofairshipaerodynamicforcesandtorquesusingextendedkalmanfilter |