Generation of a reduced-order LPV/LFT model from a set of large-scale MIMO LTI flexible aircraft models

In the civilian aviation industry, the aeroelastic behavior of an aircraft is of:en modeled at frozen flight and mass configurations using high fidelity numerical tools. Unfortunately, the resulting large-scale models cannot be handled in such form by modern analysis and control techniques, which generally require the considered models to be written as low-order Linear Fractional Representations (LFR). In this context, a methodology is described to derive a reduced-order Linear Parameter Varying (LPV) model from a reference set of large-scale Multiple Input Multiple Output (MIMO) Linear Time Invariant (LTI) models describing a given system at frozen configurations. The proposed approach is in two steps. The reference models are first reduced using recent advances in Krylov methods, leading to a set of low-order state-space representations with consistent state vectors. An LPV model is then obtained by polynomial approximation and converted into an LFR of reasonable size. A special effort is made to avoid data overfitting by using as simple as possible approximation formulas. The method is applied to a long-range commercial aircraft model developed in an industrial context: a set of large-scale flexible models linearized at different mass configurations is converted into a single low-order LPV model. More generally, any kind of purely numerical models for which the analytical structure is unknown can be considered. (C) 2012 Elsevier Ltd. All rights reserved.