First Approach to Coupling of Numerical Lifting-Line Theory and Linear Covariance Analysis for UAV State Uncertainty Propagation

Authors

Cory D. Goates, Utah State UniversityFollow
Randall S. Christensen, Utah State UniversityFollow
Robert C. Leishman, Air Force Institute of Technology

Document Type

Article

Publication Date

Summer 2019

Abstract

Numerical lifting-line is a computationally efficient method for calculating aerodynamic forces and moments on aircraft. However, its potential has yet to be tapped for use in guidance, navigation, and control (GN&C). Linear covariance analysis is becoming a popular GN&C design tool and shows promise for pairing with numerical lifting-line. Pairing numerical lifting-line with linear covariance analysis allows for forward propagation of state uncertainty for real-time decision making. We demonstrate this for select state variables in a drone aerial recapture situation. Linear covariance analysis uses finite difference derivatives obtained from numerical lifting-line to calculate force and moment variances. These show agreement with Monte Carlo simulation results to within 10%, without the significant computational cost of Monte Carlo. These results show numerical lifting-line can be used in linear covariance analysis of an entire UAV GN&C solution. Not only does this allow for real-time uncertainty propagation, but also faster and more thorough multi-disciplinary design optimization.

Comments

Report from Summer Faculty Fellowship, 2019

Recommended Citation

Goates, C. D., Christensen, R.S., and Leishman, R.C., "First Approach to Coupling of Numerical Lifting-Line Theory and Linear Covariance Analysis for UAV State Uncertainty Propagation", ANT Center Tech Report, 2019.