Parameter identification experiments deliver an identified model together with an ellipsoidal
uncertainty region in parameter space. The objective of robust controller design is thus to …

We propose a model validation procedure that consists of a prediction error identification
experiment with a full order model. It delivers a parametric uncertainty ellipsoid and a …

(*) Notice: Subject to any disclaimer the term of this ings of the 32nd Conference on Decision
and Control, Dec. 1993.* patent is extended or adjusted under 35 Van den Hof," Closed …

This paper considers two robustly convergent algorithms for the identification of a linear
system from (possibly) noisy frequency response data. Both algorithms are based on the …

In approximate identification, the goal of the model should be taken into account when
evaluating model quality. The purpose of this paper is the development of a system …

With the long-term running of an on-orbit satellite, parameters in its attitude model are
naturally altered due to the wastage of on-board components and the consumption of …

This work proposes a unified algorithm for identification and control. Frequency domain data
of the plant is weighted to satisfy the given performance specifications. A model is then …

Frequency response estimation from closed-loop time-domain experimental data is
investigated in this paper for normalized coprime factors (NCF) of a multiple-input-multiple …

This paper presents a robust-control-oriented system identification method aiming to
minimize the normalized coprime factor uncertainty of the performance-weighted system …

Several techniques related to control design rely on parametric system models. In the
industry of servo control commissioning these techniques are not well established, mostly …