Rescaling State and Input Variables for the Purpose of Analyzing Process Models

Many techniques which are used for analyzing the structure of large-scale, interactive systems (including structural dominance analysis and the singular value decomposition method) require a careful scaling of input and state variables to yield useful results. A suitable scaling procedure motivated by physical arguments is presented and illustrated through several examples, including linear and nonlinear as well as lumped and distributed parameter models.