This paper deals with the identification of stochastic loads applied to a nonlinear dynamical system for which a few experimental responses are available using an uncertain computational model. Uncertainties are induced by the use of a simplified computational model to predict the responses of the real system. A nonparametric probabilistic approach of both parameter uncertainties and model unce...

A detailed uncertainty analysis is presented for the pulse parameter measurement service of the National Institute of Standards and Technology (NIST, USA). It relates to the new pulse parameter measurement and extraction processes. Uncertainties for pulse amplitude, transition duration, overshoot and undershoot (preshoot) are given. Effects of temperature variation, impulse response estimate, p...

The importance of taking model uncertainties into account during controller design is well established. Although this theory is well developed and quite mature, the worst-case uncertainty descriptions assumed in robust control formulations are incompatible with the uncertainty descriptions generated by commercial model identification software that produces time-invariant parameter uncertainties...

In this paper, we mainly study the robust stability of linear continuous systems with parameter uncertainties, a more general kind of uncertainties for system matrices is considered, i.e., entries of system matrices are rational functions of uncertain parameters which are varying in intervals. we present a method which can check the robust Hurwitz stability of such uncertain systems in finite s...

This paper considers the problem of estimation and identification with bounded uncertainties in the data and system matrices. In particular, we will examine how to solve the Ax ≈ b when we have bounds on the errors of column blocks of A in the min max sense. Error bounds on column blocks of the system matrix A are caused by numerous situations, such as different sensor or parameter uncertaintie...