An Aircraft Application of System Identification in the Presence of State Noise.
CALIFORNIA UNIV LOS ANGELES DEPT OF SYSTEM SCIENCES
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A maximum likelihood estimator for a linear system with state and observation noise is developed to determine unknown aircraft coefficients from flight data in the presence of turbulence state noise. The formulation of the algorithm is presented briefly. The linear equations for an aircraft in atmospheric turbulence are defined. The effectiveness and accuracy of the technique are assessed by first applying it to simulated flight data, in which the true parameter values are known, then to actual flight data obtained in turbulence. A complete set of aircraft coefficients is obtained as well as an estimate of the turbulence time history. The validity of the estimated state noise and of the estimated coefficients is tested. The feasibility of using the algorithm for defining an adaptive control law to alleviate the effects of turbulence on the aircraft is discussed.
- Theoretical Mathematics