Complementary use of black-box and physics-based techniques in rotorcraft system identification

Abstract

Accurate linear helicopter models are needed for control system development and simulation and can be determined by system identi1cation when appropriate test data are available. Standard methods for rotorcraft system identi1cation are the frequency domain maximum likelihood method and the frequency response method that are used to derive physics-based linear state-space models. But also the optimized predictor-based subspace identi1cation method (PBSIDopt), a time domain system identi1cation method that yields linear black-box state-space models, has been successfully applied to rotorcraft data. As both methods have their respective strengths and weaknesses, it was tried to combine both techniques. The paper demonstrates the successful complementary use of physics-based frequency domain methods and the black-box PBSIDopt method in the areas of database requirements, accuracy metrics, and model structure development using 2ight test data of DLR's ACT/FHS research rotorcraft.