다변수 스토캐스틱 선형 계통의 추정에 관한 연구

On the identification of the multivariable stochastic linear systems

The problem of parameter identification for multivariable stochastic linear systems from output measurements, which are corrupted by noises, is considered. A modified Luenberger's input/output canonical form is used for reducing the number of unknown coefficients. A computationally and conceptionally simple systematic procedure for parameter estimation is obtained using output correlation method. The estimates are shown to be asymptotically normal, unbiased and consistent. Numerical examples are presented to illustrate the identification method.