论文信息 - Reduction of linear continuous-time multivariable systems by matching first- and second-order information

Reduction of linear continuous-time multivariable systems by matching first- and second-order information

This paper considers the approximation of stable continuous-time multivariable linear systems from a finite number of Markov parameters and second-order information indexes. It is shown that, by properly choosing these indexes, it is possible to uniquely identify an input-output model of given order from an equal number of first- and second-order data. >

[1] R. Skelton,et al. Linear system approximation via covariance equivalent realizations , 1985 .

[2] E. Jonckheere,et al. Combined sequence of Markov parameters and moments in linear systems , 1989 .

[3] Adhemar Bultheel,et al. Pade´ techniques for model reduction in linear system theory: a survey , 1986 .

[4] R. Roberts,et al. The use of second-order information in the approximation of discreate-time linear systems , 1976 .

[5] B. Anderson,et al. The generation of all q-Markov covers , 1987 .

[6] Gian Antonio Mian,et al. Stability preservation and computational aspects of a newly proposed reduction method , 1988 .

[7] Victor Sreeram,et al. Identification and model reduction from impulse response data , 1990 .

[8] Yujiro Inouye,et al. Approximation of multivariable linear systems with impulse response and autocorrelation sequences , 1983, Autom..

[9] Brian D. O. Anderson,et al. Weighted q-Markov covariance equivalent realizations , 1989 .

[10] T. N. Lucas. Continued-fraction algorithm for biased model reduction , 1983 .