Graduation Semester and Year
2014
Language
English
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Aerospace Engineering
Department
Mechanical and Aerospace Engineering
First Advisor
Atilla Dogan
Abstract
This dissertation work develops a method for onboard estimation of wind field with spatial and temporal variation based on local wind vector estimation and/or measurements from multiple aircraft flying in the same airspace. Aircraft flying in the same airspace of operation are considered airborne wind sensors scattered over the airspace because of the fact that aircraft carry along with them wind information inherent in their dynamics and kinematics. The onboard wind field estimation is formulated in the framework of parameter estimation based on various wind field models, which are different function of position and time. The online wind field estimation is utilized in trajectory prediction of aircraft in spatially and temporally varying wind. Various simulation cases are presented to demonstrate the feasibility of wind field estimation and the benefit of using such information in trajectory prediction. Further this dissertation presents a method of input prediction for and aircraft flying in spatially and temporally varying wind field. Input prediction is done using inverse simulation to compute the required control variables (control surface deflections and thrust level) for an aircraft to fly through a prescribed trajectory. Estimated wind field is also used in inverse simulation for input prediction as in the trajectory prediction case. Various simulation cases are presented to demonstrate the feasibility of input prediction method and the importance of including wind field information in inverse simulations.
Disciplines
Aerospace Engineering | Engineering | Mechanical Engineering
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Kampoon, Jane-wit, "Wind Field Estimation And Its Utilization In Trajectory And Input Prediction" (2014). Mechanical and Aerospace Engineering Dissertations. 70.
https://mavmatrix.uta.edu/mechaerospace_dissertations/70
Comments
Degree granted by The University of Texas at Arlington