This paper presents theory, algorithms and validation results for system identification of continuous-time state-space models from finite non-uniformly sampled input-output sequences. The algorithms developed are methods of model identification and stochastic realization adapted to the continuous-time model context using non-uniformly sampled input-output data. The resulting model can be decompose

This study explores how democracy—often understood as an abstract concept or a location- transcending, intangible phenomenon—is produced, shaped and continuously reshaped through local library practices in certain places and under local conditions at a specific point in time. To better understand potential conflicts and/or tensions that might arise between the three levels of Swedish library polic

This paper offers a two-zone, physical, NOx model with low computational cost, implemented in C on an embedded system. The model is able to compute NOx-emission formation with high time resolution during an engine cycle. To do this the model takes cylinder pressure and injected fuel amount as inputs and produces NO concentration as output. The model as such is not new, nevertheless the physical ba

The paper describes an on-line identification algorithm to estimate the steam production of a municipal solid waste incinerator. The algorithm has to learn on-line the system dynamics due to the heavy disturbances acting on the incineration process. The learning algorithm is based on radial basis function networks and combines the growth criterion of the resource allocating network technique with

Bakgrund: I samband med en workshop om att jobba i lärplattformen Canvas så inledde tre bibliotekarie vid Lunds universitet ett projekt att skapa en resurs för referenshanteringsprogrammet EndNote. Vi började i januari 2020 och lanserade vår Canvas-kurs med EndNote X9 i augusti 2020. Under 2021 uppdaterades hela kursen för att anpassas till EndNote 20.Syfte: Syftet var att täcka en lucka, då vi sa

Recursive estimation in feedback operation as used in minimum variance adaptive control is considered. The paper uses Lyapunov theory and supermartingale analysis to is to remove the stochastic stability assumption in previous work.

Children are particularly sensitive to air pollution exposure, and their personal exposures may differ significantly from those of adults. One key factor for understanding the personal inhaled dose of air pollutants is the respiratory minute ventilation (Ve). To estimate the amount of particles circulated through the lungs, 24 h averages of Ve are often used. These averages poorly capture variatio

The problem of adaptive prediction and direct adaptive control for systems described by delay-differential systems is considered. A model reference approach to direct adaptive control is shown to be feasible for a class of 2-D systems. A reparametrization of the 2-D system description is given and the identification problem is converted into a linear estimation problem. Some necessary conditions f