Flutter-Prediction Tool for Flight-Test-Based Aeroelastic Parameter-Varying Models

Abstract

In this work, a parameter-varying estimation framework is proposed to increase the efficiency offlight testing. The framework generates a set of tools to rapidly evaluate parameters required to certify an aircraft during envelope expansion. The primary innovation is a generalized aeroelastic parameter-varying framework that allows for a variety of approaches and test procedures. The framework considers the variations of aircraft parameters due to flight conditions. The core algorithms are based on the well-developed linear fractional transformation algebra and analysis for aeroelastic/aeroservoelastic systems. They are built upon an integrated parameter-estimation framework that is robust enough to tolerate real-world flight-testing 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. In the second case study, flight-test data from the Aerostructure Test Wing program were used to demonstrate the feasible application of the core algorithms using data coming from actual flight-test programs.