Abstract
An airship is lighter than an air vehicle with enormous potential in applications such as communication, aerial inspection, border surveillance, and precision agriculture. An airship model is made up of dynamic, aerodynamic, aerostatic, and propulsive forces. However, the computation of aerodynamic forces remained a challenge. In addition to aerodynamic model deficiencies, airship mass matrix suffers from parameter variations. Moreover, due to the lighter-than-air nature, it is also susceptible to wind disturbances. These modeling issues are the key challenges in developing an efficient autonomous flight controller for an airship. This article proposes a unified estimation method for airship states, model uncertainties, and wind disturbance estimation using Unscented Kalman Filter (UKF). The proposed method is based on a lumped model uncertainty vector that unifies model uncertainties and wind disturbances in a single vector. The airship model is extended by incorporating six auxiliary state variables into the lumped model uncertainty vector. The performance of the proposed methodology is evaluated using a nonlinear simulation model of a custom-developed UETT airship and is validated by conducting a kind of error analysis. For comparative studies, EKF estimator is also developed. The results show the performance superiority of the proposed estimator over EKF; however, the proposed estimator is a bit expensive on computational grounds. However, as per the requirements of the current application, the proposed estimator can be a preferred choice.
Highlights
An airship has some unique and promising characteristics, making it a favorite among air vehicles, which led to its reemergence after 60 years of silence
Where m, mx, my, mz, Jx, Jy, Jz, Jxz are the terms corresponding to the airship mass and inertia and are given in S1 Appendix. are the coordinates of Center of Gravity (CG) with respect to Center of Volume (CV). α and β are the angle of attack and sideslip angles, respectively
The performance of the proposed estimator has been verified by developing the simulation environment for the experimental UETT airship under the autonomous UAV development project for environmental monitoring tasks
Summary
An airship is a lighter-than-air, buoyancy-driven vehicle that gains its lift from low-density gas such as helium or hydrogen. Some researchers have suggested nonlinear filter-based estimation approaches to avoid the expensive wind tunnel experiments and address the limitations of computational aerodynamic calculation methods. They have estimated the aerodynamic coefficients or the complete aerodynamic model. These estimation methods are a good cost-effective solution for approximating the airship aerodynamic model They do not consider the model uncertainties due to variation in the airship mass matrix parameters and wind disturbances. The method estimates the airship states and the combined uncertainty vector incorporating mass matrix variations, aerodynamic model deficiencies, and wind forces. The proposed approach is validated by conducting extensive simulations and considering three cases where the lumped model uncertainty vector estimates the mass matrix variations, aerodynamic model deficiencies, and wind disturbances. The same problem is solved using the EKF estimator
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