Frequency response function identification of periodically scheduled linear parameter-varying systems

• A class of identifiable frequency response function models is developed for linear parameter-varying systems. closed-form Jacobian the weighted nonlinear least-squares estimator derived. An experimental LPV FRF model a flexible beam system estimated. The estimate shows high simulation performance on validation data sets. For Linear Time-Invariant (LTI) systems, Frequency Response Functions (FRFs) facilitate dynamics analysis, controller design, and parametric modeling, while many practically relevant systems are in fact more accurately described by Parameter-Varying (LPV) models. aim this paper to develop an modeling framework periodically scheduled Single-Input Single-Output (SISO) that enables identification from global experiments. This achieved developing appropriate definition harmonic input–output method compute suitable estimator. approach generalizes Empirical Transfer Function Estimate (ETFE) periodically-scheduled classical ETFE recovered LTI as special case. successfully used SISO motion system, thereby confirming potential framework.