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This work presents the results of experimental operation of a solar-driven climate system using mixed-integer nonlinear model predictive control (MPC). The system is installed in a university building and consists of two solar thermal collector fields, an adsorption cooling machine with different operation modes, a stratified hot water storage with multiple inlets and outlets as well as a cold water storage. The system and the applied modeling approach is described and a parallelized algorithm for mixed-integer nonlinear MPC and a corresponding implementation for the system are presented. Finally, we show and discuss the results of experimental operation of the system and highlight the advantages of the mixed-integer nonlinear MPC application.
The identification and quantification of compounds in the gas phase becomes of increasing interest in the context of environmental protection, as well as in the analytical field. In this respect, the high extinction coefficients of vapours and gases in the ultraviolet wavelength region allow a very sensitive measurement system. In addition, the increased performance of the components necessary for setting up a measurement system, such as fibres, light sources and detectors has been improved. In particular the light sources and detectors offer improved stability, and the deep UV performance and solarisation resistance of fused silica fibres allow have been significantly optimized in the past years. Therefore a compact and reliable detection system with high measuring accuracy is developed. Within this paper possible applications of the system under development and recent results will be discussed.