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

Abstract

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 equiv- alent 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.