Estimation of gramian-based interaction measures for weakly nonlinear systems

A critical step in the control design of industrial processes is the Control Configuration Selection (CCS), where each actuator is grouped with a set of measurements to be used in the computation of its control action. Tools for CCS include gramian-based Interaction Measures (IMs), initially defined for linear systems. Since a trending research topic is the derivation of IMs for nonlinear systems, a decision of the designer is therefore the approach to the problem in the linear or nonlinear framework. For this end, a method is discussed that determines the degree of nonlinearity of a system based on a specially tailored experiment, and thus enables the selection of the correct framework for the analysis. The novelty is in the estimation of two gramian-based IMs with confidence bounds from the tailored experiment which is applicable if the process is revealed to be weakly nonlinear.