Model order reduction of LPV systems based on parameter varying modal decomposition

The model reduction problem of high dimensional Linear Parameter Varying (LPV) systems is addressed in the paper. Modal representation of local systems is computed first for fixed values of the scheduling parameter. Modes are then matched and a smooth quasi-modal form is obtained over the entire parameter domain. Classification of system modes is applied to explore dynamic coherence of the model. Structured parameter-varying Gramians are constructed and used for balancing the model and eliminating negligible components. Numerical example illustrates the effectiveness of the methodology.