Model-based control design plays a key role in today's industrial practice, and industry
demands cuttingedge methods for identifying the necessary models. However, additional …

In this paper, a novel method is proposed to design a free final time input signal, which is
then used in the robust system identification process. The solution of the constrained optimal …

Abstract Model-based operation support technology such as Model Predictive Control
(MPC) is a proven and accepted technology for multivariable and constrained large scale …

Experiment Design for system identification involves the design of an optimal input signal
with the purpose of accurately estimating unknown parameters in a system. Specifically, in …

System identification is a process that can be achieved in many different ways. The
fundamental idea is to excite a process under operation and use the observed response to …

The ability to obtain the maximum amount of information from a system while achieving the
desired control performance highly depends on the applied excitation signal. In this work, a …

This thesis is divided into two main parts. The first part considers application-oriented input
design, specifically for model predictive control (MPC). The second part considers …

The optimal input signal design is a procedure of generating an informative excitation signal
to extract the model parameters with maximum accuracy during the estimation process. Non …

An optimal feedback input design method for active parameter identification of dynamic
nonlinear systems is presented. The problem is formulated in a receding horizon framework …

Least-costly experiment design has received ample attention over the past decades, and
efficient numerical algorithms that can compute optimal excitation spectra for linear models …