Publications

Time-periodic (TP) phenomena occurring, for instance, in wind turbines, helicopters, anisotropic shaft-bearing systems, and cardiovascular/respiratory systems, are often not addressed when classical frequency response function (FRF) measurements are performed. As the traditional FRF concept is based on the linear time-invariant (LTI) system theory, it is only approximately valid for systems with varying dynamics. Accordingly, the quantification ...

The consequences of estimating the frequency response function of a continuous-time, linear time-varying (LTV) system with tools for linear time invariant (LTI) systems are studied. To this end, the best linear time invariant approximation of an LTV system is defined, and is related to a general model for LTV systems. A recently introduced frequency response function estimation method for LTI systems is used to compute the best linear time ...

A Wiener model is a fairly simple, well known, and often used nonlinear block-oriented black-box model. A possible generalization of the class of Wiener models lies in the parallel Wiener model class. This paper presents a method to estimate the linear time-invariant blocks of such parallel Wiener models from input/output data only. The proposed estimation method combines the knowledge obtained by estimating the best linear approximation of a ...

Time-periodic (TP) phenomena occurring, for instance, in wind turbines, helicopters, anisotropic shaftbearing systems, reciprocating engines, ... are often not addressed when classical frequency response function (FRF) measurements are performed. As the traditional FRF concept is based on the linear time-invariant (LTI) system theory, it is only approximately valid for systems with varying dynamics. Accordingly, the quantification of any ...

Linear system identification [1]?[4] is a basic step in modern control design approaches. Starting from experimental data, a linear dynamic time-invariant model is identified to describe the relationship between the reference signal and the output of the system. At the same time, the power spectrum of the unmodeled disturbances is identified to generate uncertainty bounds on the estimated

Time-periodic (TP) phenomena occurring, for instance, in wind turbines, helicopters, anisotropic shaft-bearing systems, and cardiovascular/respiratory systems, are often not addressed when classical frequency response function (FRF) measurements are performed. As the traditional FRF concept is based on the linear time-invariant (LTI) system theory, it is only approximately valid for systems with varying dynamics. Accordingly, the quantification ...

Nonparametric frequency response function (FRF) estimates are a standard tool to get quickly insight into the dynamic behavior of complex systems. However, in quite some applications the time-invariance assumption is not exactly met. Therefore, it is important to detect and quantify the deviation from the ideal time-invariant framework that is inherent to the concept of an FRF. In this paper we present a new (direct) method for estimating the ...

The consequences of estimating the frequency response function of a continuous-time, linear time-varying (LTV) system with tools for linear time invariant (LTI) systems are studied. To this end, the best linear time invariant approximation of an LTV system is defined, and is related to a general model for LTV systems. A recently introduced frequency response function estimation method for LTI systems is used to compute the best linear time ...

Block-oriented model structure detection is quite desirable since it helps to imagine the system with real physical elements. In this paper, we explore experimental methods to detect the internal structure of the system, using a black box approach. Two different strategies are compared and the best combination of these is introduced. The methods are applied on two real systems with a static nonlinear block in the feedback path. The main goal is ...

In many engineering applications, linear models are preferred, even if it is known that the system is disturbed by nonlinear distortions. A large class of nonlinear systems, which are excited with a "Gaussian" random excitation, can be represented as a linear system GBLA plus a nonlinear noise source YS. The nonlinear noise source represents that part of the output that is not captured by the linear approximation. In this paper, it is shown that ...