A Framework for Structural Input/Output and Control Configuration Selection in Large-Scale Systems
This paper addresses problems on the structural design of large-scale control systems. An efficient and unified framework is proposed to select the minimum number of manipulated/ measured variables to achieve structural controllability/ observability of the system, and to select the minimum number of feedback interconnections between measured and manipulated variables such that the closed-loopsystem has no structural fixed modes. Global solutions are computed using polynomial complexity algorithms in the number of the state variables of the system. Finally, graph-theoretic characterizations are proposed, which allow a characterization of all possible solutions.