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This paper addresses problems on the structural design of control systemstaking explicitly into consideration the possible application to large-scalesystems. We provide an efficient and unified framework to solve the followingmajor minimization problems: (i) selection of the minimum number ofmanipulated/measured variables to achieve structuralcontrollability/observability of the system, and (ii) selection of the minimumnumber of feedback interconnections between measured and manipulated variablessuch that the closed-loop system has no structurally fixed modes. Contrary towhat would be expected, we show that it is possible to obtain a global solutionfor each of the aforementioned minimization problems using polynomialcomplexity algorithms in the number of the state variables of the system. Inaddition, we provide several new graph-theoretic characterizations ofstructural systems concepts, which, in turn, enable us to characterize allpossible solutions to the above problems.

A Framework for Structural Input/Output and Control Configuration Selection in Large-Scale Systems