The Application of Expectation Maxmization Algorithm in Aircraft Flutter Model Parameter Identification

The traditional least-squares identification method gives biased parameter estimates when the observed input-output data are corrupted by noises.A general EM algorithm is adopted for aircraft flutter model parameter identification under the noisy environment.The EM algorithm is an iterative algorithm based on the stochastic state space model.It is used to compute the maximum value for the likelihood function that consists of two steps: namely the E-and M-steps.No calculation of the second order derivatives or approximated values is needed.This algorithm can increase the likelihood function converging to a stationary point.Before applying the algorithm,the innovation variance criterion is used to estimate the system's order in order to decrease the complexity.Finally the efficiency of this method is illustrated with a simulation example.