The benchmark Active Vibration Isolation System (AVIS) in this paper is a complex high-tech industrial system used in vibration and motion control applications. The system is complex in the sense of high order flexible dynamics and multiple inputs and outputs. The aim of this benchmark is to compare different black box, linear time invariant system identification algorithms. Different large data sets are provided, enabling the use of both frequency domain and time domain identification approaches. The idea of the benchmark is to investigate both model accuracy and numerical reliability of the computational steps. Several reference solutions are provided, which demonstrate the challenging aspects of this benchmark already in the singleinput single-output case. The benchmark data and additional info are available on the website of Tom Oomen 1 .
The aim of this work is the evaluation of two stateestimators in a glucose estimation in a diabetes control setting. Technological solutions leading to the design of an artificial pancreas heavily rely on the availability of glucose subcutaneously. Practical solutions for these measurements often suffer from significant time-delays and direct measurements of the required states is often impossible. This complicates the prediction of the required insulin dose, leading to fixed glucose intake patterns for the patient, i.e., a fixed diet at predefined times during the day. This paper describes a state-estimation approach to deal with the large time-delays, which enables relaxations of the restrictions on the patients glucose intake. Based on two models, widely used within the medical society, multiple Kalman-based filtering techniques are compared.A. van Rietschoten and R. van der Maas are with the
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