Nonlinear estimation of aircraft models for on-line control customization

• Published in: 2001 IEEE Aerospace Conference Proceedings (Cat. No.01TH8542) Vol. 2; pp. 2/621 - 2/628 vol.2
• Main Authors: Campbell, M.E., Brunke, S.
• Format: Conference Proceeding Journal Article
• Language: English
• Published: IEEE 01.03.2001
• Subjects: Aerodynamics; Aerospace control; Aircraft propulsion; Atmospheric modeling; Automatic control; Control systems; Parameter estimation; Remotely operated vehicles; State estimation; Vehicle dynamics
• ISBN: 0780365992; 9780780365995
• ISSN: 1095-323X
• DOI: 10.1109/AERO.2001.931241

This paper describes a new nonlinear estimation procedure used to estimate and track the parameters of a nonlinear aircraft. The Unscented Kalman Filter (UKF) is developed and compared to the more traditional Extended Kalman Filter (EKF). State and parameters are estimated on the F-15 for both a complex maneuver and a maneuver with failure. The algorithms have access to the nonlinear dynamic equations, but not the aircraft engine models, aerodynamic models, or atmospheric models. Parameters describing these unknown dynamics are estimated in the EKF and UKF algorithms. Results show the UKF to be more accurate than the EKF, and track all parameters very well at all times, even after a 50% failure of the stabilator. The aerodynamic forces and moments, while difficult to track immediately after the failure because of the discontinuous nonlinearity, did recover quickly and stay within the predicted bounds.