Q-Markov covariance equivalent realization and its application to flexible structure identification

The Q-Markov covariance equivalent realization algorithm is applied to NASA's Minimast structure to identify state-space models for the purpose of designing closed-loop controllers, and laboratory test results are shown for the identification and for the closed-loop performance. The paper also presents for the first time a deterministic formulation of covariance parameters from a pulse response, a stochastic formulation of Markov parameters from a white-noise response, and a simple Q-Markov covariance equivalent realization formulation. This requires only pulse laboratory tests or only white-noise laboratory tests to generate Q-Markov covariance equivalent realizations.

[1]  B. Anderson The inverse problem of stationary covariance generation , 1969 .

[2]  J. Rissanen,et al.  1972 IFAC congress paper: Partial realization of random systems , 1972 .

[3]  Thomas Kailath,et al.  Linear Systems , 1980 .

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

[5]  K. Glover All optimal Hankel-norm approximations of linear multivariable systems and their L, ∞ -error bounds† , 1984 .

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

[7]  Jitendra Tugnait Order reduction of SISO nonminimum phase stochastic systems , 1985, 1985 24th IEEE Conference on Decision and Control.

[8]  Jer-Nan Juang,et al.  An eigensystem realization algorithm for modal parameter identification and model reduction. [control systems design for large space structures] , 1985 .

[9]  R. Skelton,et al.  A projection approach to covariance equivalent realizations of discrete systems , 1986 .

[10]  U. B. Desai,et al.  A Generalized Approach to q-Markov Covariance Equivalent Realizations for Discrete Systems , 1987, 1987 American Control Conference.

[11]  Yoram Baram,et al.  Identification of minimal order state models from stochastic input-output data , 1988 .

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

[13]  J. H. Kim,et al.  An Iterative Algorithm Combining Model Reduction and Control Design , 1990, 1990 American Control Conference.

[14]  Ketao Liu Q-Markov Cover identification and integrated MCA-OVC controller design for flexible structures , 1991 .

[15]  R. Skelton,et al.  Modeling Hubble Space Telescope Flight Data by Q-Markov Cover Identification , 1992, 1992 American Control Conference.

[16]  Robert E. Skelton,et al.  Integrated modeling and controller design with application to flexible structure control , 1993, Autom..