Nonlinear analysis of stability and control for an F-16 configuration

1997 ◽  
Author(s):  
Zhongjun Wang ◽  
Zhidai He ◽  
C. Lan ◽  
Zhongjun Wang ◽  
Zhidai He ◽  
...  
Keyword(s):  
Nonlinear Analysis ◽  
Stability And Control ◽  
Analysis Of Stability ◽  
And Control

scholarly journals Analysis of Stability and Control in Landfill Sites Expansion

2011 ◽  
Vol 24 ◽  
pp. 667-671 ◽  
Author(s):  
Fang Rong ◽  
Guo Zhaogui ◽  
Feng Tugen
Keyword(s):  
Stability And Control ◽  
Landfill Sites ◽  
Analysis Of Stability ◽  
And Control

Designing Stability and Control Augmentation Systems Using Genetic Algorithms

2009 ◽  
Author(s):  
Ashraf Omran ◽  
Mohamed Elshabasy ◽  
Wael Mokhtar ◽  
Brett Newman ◽  
Mohamed Gharib
Keyword(s):  
Genetic Algorithms ◽  
Stability And Control ◽  
And Control

scholarly journals Method for designing multi-input system identification signals using a compact time-frequency representation

2021 ◽  
Author(s):  
Mathias Stefan Roeser ◽  
Nicolas Fezans
Keyword(s):  
System Identification ◽  
Design Method ◽  
Flight Test ◽  
Compact Representation ◽  
Time Frequency ◽  
Stability And Control ◽  
Frequency Representation ◽  
Aerodynamic Parameters ◽  
Definition Of ◽  
And Control

AbstractA flight test campaign for system identification is a costly and time-consuming task. Models derived from wind tunnel experiments and CFD calculations must be validated and/or updated with flight data to match the real aircraft stability and control characteristics. Classical maneuvers for system identification are mostly one-surface-at-a-time inputs and need to be performed several times at each flight condition. Various methods for defining very rich multi-axis maneuvers, for instance based on multisine/sum of sines signals, already exist. A new design method based on the wavelet transform allowing the definition of multi-axis inputs in the time-frequency domain has been developed. The compact representation chosen allows the user to define fairly complex maneuvers with very few parameters. This method is demonstrated using simulated flight test data from a high-quality Airbus A320 dynamic model. System identification is then performed with this data, and the results show that aerodynamic parameters can still be accurately estimated from these fairly simple multi-axis maneuvers.

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