MULTIDIMENSIONAL REALIZATION OF LARGE SCALE UNCERTAIN SYSTEMS FOR MULTIVARIABLE STABILITY MARGIN COMPUTATION

SUMMARY The prevailing framework for robust stability and performance analysis requires that the uncertain system be written as a linear fractional transformation of the uncertain parameters. This problem is algebraically equivalent to the problem of deriving the state space realization for a multidimensional transfer function matrix, for which a systematic algorithm was recently provided by Cheng and DeMoor. 1 In this work an algorithm is developed that reduces the dimension of the realizations while improving numerical accuracy, reducing computational expense, and reducing run-time memory requirements. Such improvements are required for the realization of large scale uncertain systems, which have large numbers of inputs, outputs, states, and=or uncertain parameters.