Robust Flutter Prediction for Data-Based Aeroelastic LPV Models

3253 In this work a Parameter-Varying Estimation (PVE) framework is proposed to increase efficiency of flight testing. This framework will generate a set of tools that will rapidly evaluate parameters that are required to certify an aircraft during envelope expansion. The primary innovation is a generalized aeroelastic Linear Parameter Varying (LPV) framework that admits a variety of approaches and test procedures. This framework considers the variations of aircraft parameters due to flight conditions. The core algorithms are based on the well developed LFT algebra and µ analysis for aeroelastic/aeroservoelastic systems. They are built upon an integrated parameter estimation framework that proved to be robust enough to tolerate real flight te sting environments. Two application cases were successfully solved using the algorithms developed during this work. The first case study involved a generic pitch and plunge linear aeroelastic wind-tunnel model whereas flight-test data from the Aerostructure Test Wing (ATW) program was used to demonstrate the feasible application of the prototypical core algorithms using data coming from actual flight-test programs.