In many engineering applications the level of nonlinear distortions in frequency response function (FRF) measurements is quantified using specially designed periodic excitation signals called random phase multisines and periodic noise. The technique is based on the concept of the best linear approximation (BLA) and it allows one to check the validity of the linear framework with a simple experiment. Although the classical BLA theory can handle measurement noise only, in most applications the noise generated by the system – called process noise – is the dominant noise source. Therefore, there is a need to extend the existing BLA theory to the process noise case. In this paper we study in detail the impact of the process noise on the BLA of nonlinear continuous-time systems operating in a closed loop. It is shown that the existing nonparametric estimation methods for detecting and quantifying the level of nonlinear distortions in FRF measurements are still applicable in the presence of process noise. All results are also valid for discrete-time systems and systems operating in open loop.
Original languageEnglish
Pages (from-to)8600-8612
Number of pages13
JournalIEEE Transactions on Instrumentation and measurement
Issue number10
Early online dateApr 2020
Publication statusPublished - Oct 2020

    Research areas

  • best linear approximation, nonlinear systems, feedback, continuous-time, process noise, nonparametric estimation, frequency response function

ID: 51476492