2015
DOI: 10.1016/j.ifacol.2015.11.318
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NMPC for superfluid helium cryogenics

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Cited by 4 publications
(3 citation statements)
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“…A complete approach to development of Output-feedback on-line NMPC based on relatively complex first-principles models is presented in Chapters 6 and 7 and by Noga et al (2015). It enables application of non-linear predictive control and Moving Horizon Estimation to complex, large scale systems described using distributed parameters models with stiff dynamics that are characterized by high computational cost of simulation.…”
Section: Contributionsmentioning
confidence: 99%
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“…A complete approach to development of Output-feedback on-line NMPC based on relatively complex first-principles models is presented in Chapters 6 and 7 and by Noga et al (2015). It enables application of non-linear predictive control and Moving Horizon Estimation to complex, large scale systems described using distributed parameters models with stiff dynamics that are characterized by high computational cost of simulation.…”
Section: Contributionsmentioning
confidence: 99%
“…Proof of concept, output-feedback NMPC application to the magnets temperature stabilization in an SHCC sub-sector at the LHC, using the innovative MHE-LO state estimator, presented in Chapter 7 and by Noga et al (2015), has been developed following the approach, implemented in C, simulated in MATLAB and experimentally implemented and tested at the LHC using WinCC OA (previously Siemens SIMATIC WinCC Open Architecture) SCADA. The control objectives have been defined, acknowledging the importance of distributed parameter nature of the circuit and the saturation temperature in the heat exchanger and the important role of the constraints on the helium supply mass flow rate.…”
Section: Contributionsmentioning
confidence: 99%
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