State decomposition for singular perturbation order reduction—A modal approach†

Abstract

Abstract Singular perturbation techniques for order reduction are based on decomposing the high-order system into two parts. Approximation of the high-order system dynamics by the low-order model is mainly dependent on this partition. This paper introduces a measure for the degree of dependence of the state variables on the high-order dominant eigenvalues. By means of this measure it is not only possible to find an appropriate decomposition yielding a good low-order model, but also to get an indication of the order of the reduced model. Two illustrative examples demonstrate the main results. Notes This work was partly supported by the Deutsche Forschungsgemeinschaft.