There are a number of peculiar aspects to parafoil and payload systems that make it difficult to apply conventional system identification procedures used for aerospace systems. Parafoil and payload systems are unique because typically there is very little sensor information available, the sensors that are available are separated from the canopy by a complex network of flexible rigging, the systems are very sensitive to wind and turbulence, the systems exhibit a number of nonlinear behaviors, and the systems exhibit a high degree of variability from flight to flight. The current work describes a robust system identification procedure developed to address the specific difficulties posed by airdrop systems. By employing a two-phase approach that separately considers atmospheric winds estimation and aerodynamic coefficient estimation, a nonlinear, 6-degree-of-freedom dynamic simulation model is generated using only Global Positioning System data from the flight test. The key to this approach is the use of a simplified aerodynamic representation of the canopy, which requires identification of only the steady-state response to control input to completely define the dynamic model. The proposed procedure is demonstrated by creating a simulation model using Global Positioning System data from actual flight tests. To validate the procedure, the dynamic response of the simulation model is then compared to inertial measurement unit data that were not used in any way to develop the simulation model, with excellent results.
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