Regime Selection in Local Modeling

Abstract

Local modeling is a useful approach for nonlinear system identification. Local models are constructed on several operating regimes, and the global system model is constructed by combining these local models with a suitable interpolation function. The models are then dependent on the choice of operating regimes. Here, we propose an algorithm to select suitable operating regimes automatically. It is based on Kullback’s discrimination information (KDI) and Akaike’s information criterion (AIC). Numerical simulation results illustrate the applicability of the proposed idea.