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Efficient operation of air-side economizer using extremum seeking control / Pengfei Li in Transactions of the ASME . Journal of dynamic systems, measurement, and control, Vol. 132 N° 3 (Mai 2010) 

Public ISBD [article]  in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 132 N° 3 (Mai 2010) . - 10 p. Titre : Efficient operation of air-side economizer using extremum seeking control Type de document : texte imprimé Auteurs : Pengfei Li, Auteur ; Yaoyu Li, Auteur ; John E. Seem, Auteur Année de publication : 2010 Article en page(s) : 10 p. Note générale : Systèmes dynamiques Langues : Anglais (eng) Mots-clés : Energy  conservation  Energy  consumption  HVAC  Optimal  control Index. décimale : 629.8 Résumé : As the heating, ventilating, and air conditioning (HVAC) systems accounts for a major sector of energy consumption for commercial buildings, there has been a greater demand for improving the efficiency of such systems. The air-side economizers have been developed as a class of energy-saving HVAC devices that may increase the energy efficiency by taking advantage of outdoor air during cool or cold weather. However, many economizers do not operate in the expected manner and waste even more energy than before installation, mostly due to the unreliable sensors and actuators in practice. Better control strategy is needed for optimal and robust operation. In this paper, an extremum-seeking control (ESC) based self-optimizing strategy is proposed to minimize the energy consumption, with the feedback of chilled water supply command rather than the temperature and humidity measurements. The mechanical cooling load is minimized by seeking the optimal outdoor air damper opening in real time. Such scheme does not need temperature and humidity sensors, and depends much less on the knowledge of the economizer model. Simulation was performed on a MODELICA based transient model of a single-duct air-handling unit developed with DYMOLA and AIRCONDITIONING LIBRARY. The simulation results demonstrated the potential of using ESC to achieve the minimal mechanical cooling load in a self-optimizing manner. In addition, an antiwindup ESC scheme is proposed to handle the ESC windup issue due to actuator (damper) saturation. The simulation results validated the effectiveness of the proposed antiwindup ESC. DEWEY : 629.8 ISSN : 0022-0434 En ligne : http://asmedl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA00013200 [...] [article] Efficient operation of air-side economizer using extremum seeking control [texte imprimé] / Pengfei Li, Auteur ; Yaoyu Li, Auteur ; John E. Seem, Auteur . - 2010 . - 10 p. Systèmes dynamiques Langues : Anglais (eng) in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 132 N° 3 (Mai 2010) . - 10 p. Mots-clés : Energy  conservation  Energy  consumption  HVAC  Optimal  control Index. décimale : 629.8 Résumé : As the heating, ventilating, and air conditioning (HVAC) systems accounts for a major sector of energy consumption for commercial buildings, there has been a greater demand for improving the efficiency of such systems. The air-side economizers have been developed as a class of energy-saving HVAC devices that may increase the energy efficiency by taking advantage of outdoor air during cool or cold weather. However, many economizers do not operate in the expected manner and waste even more energy than before installation, mostly due to the unreliable sensors and actuators in practice. Better control strategy is needed for optimal and robust operation. In this paper, an extremum-seeking control (ESC) based self-optimizing strategy is proposed to minimize the energy consumption, with the feedback of chilled water supply command rather than the temperature and humidity measurements. The mechanical cooling load is minimized by seeking the optimal outdoor air damper opening in real time. Such scheme does not need temperature and humidity sensors, and depends much less on the knowledge of the economizer model. Simulation was performed on a MODELICA based transient model of a single-duct air-handling unit developed with DYMOLA and AIRCONDITIONING LIBRARY. The simulation results demonstrated the potential of using ESC to achieve the minimal mechanical cooling load in a self-optimizing manner. In addition, an antiwindup ESC scheme is proposed to handle the ESC windup issue due to actuator (damper) saturation. The simulation results validated the effectiveness of the proposed antiwindup ESC. DEWEY : 629.8 ISSN : 0022-0434 En ligne : http://asmedl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA00013200 [...]

Self-learning based centrifugal compressor surge mapping with computationally efficient adaptive asymmetric support vector machine / Xin Wu in Transactions of the ASME . Journal of dynamic systems, measurement, and control, Vol. 134 N° 5 (Septembre 2012) 

Public ISBD [article]  in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 134 N° 5 (Septembre 2012) . - 10 p. Titre : Self-learning based centrifugal compressor surge mapping with computationally efficient adaptive asymmetric support vector machine Type de document : texte imprimé Auteurs : Xin Wu, Auteur ; Yaoyu Li, Auteur Année de publication : 2012 Article en page(s) : 10 p. Note générale : Dynamic systems Langues : Anglais (eng) Mots-clés : Surge  map  Centrifugal  compressor  Asymetric  support  vector  machine  Support  vectors  selection  Gaussian  curvature Index. décimale : 629.8 Résumé : When an air compressor is operated at very low flow rate for a given discharge pressure, surge may occur, resulting in large oscillations in pressure and flow in the compressor. To prevent the damage of the compressor, on account of surge, the control strategy employed is typically to operate it below the surge line (a map of the conditions at which surge begins). Surge line is strongly affected by the ambient air conditions. Previous research has developed to derive data-driven surge maps based on an asymmetric support vector machine (ASVM). The ASVM penalizes the surge case with much greater cost to minimize the possibility of undetected surge. This paper concerns the development of adaptive ASVM based self-learning surge map modeling via the combination with signal processing techniques for surge detection. During the actual operation of a compressor after the ASVM based surge map is obtained with historic data, new surge points can be identified with the surge detection methods such as short-time Fourier transform or wavelet transform. The new surge point can be used to update the surge map. However, with increasing number of surge points, the complexity of support vector machine (SVM) would grow dramatically. In order to keep the surge map SVM at a relatively low dimension, an adaptive SVM modeling algorithm is developed to select the minimum set of necessary support vectors in a three-dimension feature space based on Gaussian curvature to guarantee a desirable classification between surge and nonsurge areas. The proposed method is validated by applying the surge test data obtained from a testbed compressor at a manufacturing plant. DEWEY : 629.8 ISSN : 0022-0434 En ligne : http://asmedl.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA000134000005 [...] [article] Self-learning based centrifugal compressor surge mapping with computationally efficient adaptive asymmetric support vector machine [texte imprimé] / Xin Wu, Auteur ; Yaoyu Li, Auteur . - 2012 . - 10 p. Dynamic systems Langues : Anglais (eng) in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 134 N° 5 (Septembre 2012) . - 10 p. Mots-clés : Surge  map  Centrifugal  compressor  Asymetric  support  vector  machine  Support  vectors  selection  Gaussian  curvature Index. décimale : 629.8 Résumé : When an air compressor is operated at very low flow rate for a given discharge pressure, surge may occur, resulting in large oscillations in pressure and flow in the compressor. To prevent the damage of the compressor, on account of surge, the control strategy employed is typically to operate it below the surge line (a map of the conditions at which surge begins). Surge line is strongly affected by the ambient air conditions. Previous research has developed to derive data-driven surge maps based on an asymmetric support vector machine (ASVM). The ASVM penalizes the surge case with much greater cost to minimize the possibility of undetected surge. This paper concerns the development of adaptive ASVM based self-learning surge map modeling via the combination with signal processing techniques for surge detection. During the actual operation of a compressor after the ASVM based surge map is obtained with historic data, new surge points can be identified with the surge detection methods such as short-time Fourier transform or wavelet transform. The new surge point can be used to update the surge map. However, with increasing number of surge points, the complexity of support vector machine (SVM) would grow dramatically. In order to keep the surge map SVM at a relatively low dimension, an adaptive SVM modeling algorithm is developed to select the minimum set of necessary support vectors in a three-dimension feature space based on Gaussian curvature to guarantee a desirable classification between surge and nonsurge areas. The proposed method is validated by applying the surge test data obtained from a testbed compressor at a manufacturing plant. DEWEY : 629.8 ISSN : 0022-0434 En ligne : http://asmedl.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA000134000005 [...]