System identification is a procedure by which a mathematical description of vehicle or component dynamic behavior is extracted from test data. System identification can be thought of as an inverse of simulation. Simulation requires the adoption of (a-priori) engineering assumptions to allow the formulation of model equations. These simulation models are then used to predict aircraft or subsystem motion. In contrast, system identification begins with measured aircraft motion and "inverts" the responses to rapidly extract a model which accurately reflects the measured aircraft motion, without making a-priori assumptions or requiring a time-consuming modeling effort. Applications of system identification results include: (1) comparison of wind tunnel and flight characteristics; (2) validation and update of simulation models; (3) handling-qualities analyses and specification compliance; (4) optimization of automatic flight control systems; and (5) vibration and aeroelastic analyses.
The U.S. Army and NASA Academic Mission Services (NAMS) jointly distribute an integrated facility for system identification based on a comprehensive frequency-response approach that is uniquely suited to the difficult problems associated with flight test data analysis. The foundation of the CIFER® approach is the high-quality extraction of a complete multi-input/multi-output (MIMO) set of non-parametric input-to-output frequency responses. These responses fully characterize the coupled characteristics of the system without a-priori assumptions. Advanced Chirp-Z transform and composite optimal window techniques developed and exercised with over 10 years of flight project applications provide significant improvement in frequency-response quality relative to standard Fast Fourier Transforms (FFTs). Sophisticated nonlinear search algorithms are used to extract a state-space model which matches the complete input/output frequency-response data set.
Key features of the CIFER® approach are:
Application modules within CIFER® allow the: