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Abstract

This paper describes a novel technique for near real time estimation of non-linear aerodynamic coefficient dependencies on one or more independent variables. It is important from the point of view of updating the aerodynamic database of six DOF simulations subsequent to flight test. The technique is validated using the six DOF simulated data. The novelty about this technique is the combined utilization of linear interpolation and recursive least squares estimation to capture nonlinear functional dependencies that makes it suitable for multidimensional near real time estimation. The technique is preceded by data compatibility check using Extended Kalman filter.

Keywords

Estimation, Nonlinear Aerodynamic Coefficients, Recursive Least Squares, Extended Kalman Filtering

Article Details

How to Cite
C. Kamali, & A.A. Pashilkar. (2023). Near Real Time Estimation of Nonlinear Aerodynamics. Journal of Aerospace Sciences and Technologies, 60(4), 237–246. https://doi.org/10.61653/joast.v60i4.2008.808

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