2 research outputs found
Best Linear Approximation of Nonlinear Continuous-Time Systems Subject to Process Noise and Operating in Feedback
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.Comment: Accepted for publication in IEEE Transactions on Instrumentation &
Measuremen