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Synergetic control for HVAC system control and VAV box fault compensation

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Synergetic control is proposed for heating, ventilating and air-conditioning (HVAC) system control. The synergetic controller is developed using the nonlinear model of the HVAC system. Occupancy information in each zone is required in the design of the controller which offers inherent comfort according to the occupancy in the zone. The stability of the building system using the proposed control is verified through the Lyapunov approach. It is also proved that the synergetic controller is robust to external disturbances. Then, synergetic theories are used to design a reconfigurable control for damper stuck failures in variable air volume (VAV) to recover the nominal performance. Simulations are provided to validate the effectiveness of the proposed controller for a three-zone building.
Rocznik
Strony
555--570
Opis fizyczny
Bibliogr. 29 poz., rys., tab., wykr.
Twórcy
  • National Engineering School of Gabes, Research Unit MACS 06/UR/11-12, University of Gabes, Rue Omar Ibn El Khattab, Gabes 6029, Tunisia
autor
  • National Engineering School of Gabes, Research Unit MACS 06/UR/11-12, University of Gabes, Rue Omar Ibn El Khattab, Gabes 6029, Tunisia
  • Research Center for Automatic Control of Nancy, CRAN UMR 7039, Lorraine University, 54500 Vandeouvre Les Nancy, France
  • National Engineering School of Gabes, Research Unit MACS 06/UR/11-12, University of Gabes, Rue Omar Ibn El Khattab, Gabes 6029, Tunisia
Bibliografia
  • [1] Afram, A. and Janabi-Sharifi, F. (2014). Theory and applications of HVAC control systems—A review of model predictive control (MPC), Building and Environment 72: 343–355.
  • [2] Afram, A. and Janabi-Sharifi, F. (2017). Supervisory model predictive controller (MPC) for residential HVAC systems: Implementation and experimentation on archetype sustainable house in Toronto, Energy and Buildings 154: 268–282.
  • [3] Aftab, M., Chen, C., Chau, C.-K. and Rahwan, T. (2017). Automatic HVAC control with real-time occupancy recognition and simulation-guided model predictive control in low-cost embedded system, Energy and Buildings 154: 141–156.
  • [4] Bai, J. and Zhang, X. (2007). A new adaptive (PI) controller and its application in (HVAC) systems, Energy Conversion and Management 48(4): 1043–1054.
  • [5] Bengea, S.C., Li, P., Sarkar, S., Vichik, S., Adetola, V., Kang, K., Lovett, T., Leonardi, F. and Kelman, A.D. (2015). Fault-tolerant optimal control of a building (HVAC) system, Science and Technology for the Built Environment 21(6): 734–751.
  • [6] Bouchama, Z., Essounbouli, N., Harmas, M., Hamzaoui, A. and Saoudi, K. (2016). Reaching phase free adaptive fuzzy synergetic power system stabilizer, International Journal of Electrical Power & Energy Systems 77: 43–49.
  • [7] Chabir, K., Sauter, D., Gayed, M.K.B. and Abdelkrim, M.N. (2008). Design of an adaptive Kalman filter for fault detection of networked control systems, 16th Mediterranean Conference on Control and Automation (MED), Ajaccio, France, pp. 1124–1129.
  • [8] Chabir, K., Sid, M.A. and Sauter, D. (2014). Fault diagnosis in a networked control system under communication constraints: A quadrotor application, International Journal of Applied Mathematics and Computer Science 24(4): 809–820, DOI: 10.2478/amcs-2014-0060.
  • [9] Chen, J. and Patton, R.J. (2012). Robust Model-based Fault Diagnosis for Dynamic Systems, Springer Science & Business Media, Norwell, MA.
  • [10] Chinde, V., Kosaraju, K., Kelkar, A., Pasumarthy, R., Sarkar, S. and Singh, N. (2017). A passivity-based power-shaping control of building HVAC systems, Journal of Dynamic Systems, Measurement, and Control 139(11): 111007.
  • [11] Darure, T., Yamé, J.-J. and Hamelin, F. (2016). Model-based fault-tolerant control of VAV damper lock-in place failure in a multizone building, 14th International Conference on Control, Automation, Robotics and Vision (ICARCV), Phuket, Tailand, pp. 1–6.
  • [12] Du, Z., Fan, B., Chi, J. and Jin, X. (2014). Sensor fault detection and its efficiency analysis in air handling unit using the combined neural networks, Energy and Buildings 72: 157–166.
  • [13] Jafarov, E.M. (2005). Design modification of sliding mode observers for uncertain MIMO systems without and with time-delay, Asian Journal of Control 7(4): 380–392.
  • [14] Jiang, Z. and Dougal, R.A. (2004). Synergetic control of power converters for pulse current charging of advanced batteries from a fuel cell power source, IEEE Transactions on Power Electronics 19(4): 1140–1150.
  • [15] Kim, W. and Katipamula, S. (2018). A review of fault detection and diagnostics methods for building systems, Science and Technology for the Built Environment 24(1): 3–21.
  • [16] Kolesnikov, A., Veselov, G. and Kolesnikov, A. (2000). Modern Applied Control Theory: Synergetic Approach in Control Theory, TRTU, Moscow/Taganrog, pp. 4477–4479.
  • [17] Kuz’menko, A., Kolesnikov, A. and Kolesnitchenko, D. (2015). Novel robust control of hydrogenerator: The synergetic approach, IFAC-PapersOnLine 48(11): 451–456.
  • [18] Medjbeur, L., Harmas, M., Benaggoune, S. and Zehar, K. (2018). An adaptive fuzzy h synergetic approach to robust control, Journal of Dynamic Systems, Measurement, and Control 140(1): 011008.
  • [19] Nusawardhana, A., Zak, S. and Crossley, W. (2007). Nonlinear synergetic optimal controllers, Journal of Guidance, Control, and Dynamics 30(4): 1134–1147.
  • [20] Patton, R.J., Frank, P.M. and Clarke, R.N. (1989). Fault Diagnosis in Dynamic Systems: Theory and Application, Prentice-Hall, Upper Saddle River, NJ.
  • [21] Qi, X., Theilliol, D., He, Y. and Han, J. (2017). An active fault-tolerant control framework against actuator stuck failures under input saturations, International Journal of Applied Mathematics and Computer Science 27(4): 749–761, DOI: 10.1515/amcs-2017-0052.
  • [22] Sauter, D. and Hamelin, F. (1999). Frequency-domain optimization for robust fault detection and isolation in dynamic systems, IEEE Transactions on Automatic Control 44(4): 878–882.
  • [23] Sauter, D., Yamé, J., Aubrun, C. and Hamelin, F. (2015). Design of fault isolation filter for control reconfiguration: Application to energy efficiency control in buildings, 23rd Mediterranean Conference on Control and Automation (MED), Torremolinos, Spain, pp. 197–202.
  • [24] Seybold, L., Witczak, M., Majdzik, P. and Stetter, R. (2015). Towards robust predictive fault-tolerant control for a battery assembly system, International Journal of Applied Mathematics and Computer Science 25(4): 849–862, DOI: 10.1515/amcs-2015-0061.
  • [25] Slotine, J.-J.E. and Li, W. (1991). Applied Nonlinear Control, Prentice Hall, Englewood Cliffs, NJ.
  • [26] Utkin, V.I. (2013). Sliding Modes in Control and Optimization, Springer Science & Business Media.
  • [27] Veselić, B., Draženović, B. and Milosavljević, Č. (2014). Sliding manifold design for linear systems with unmatched disturbances, Journal of the Franklin Institute 351: 1920–1938.
  • [28] Yu, Y., Woradechjumroen, D. and Yu, D. (2014). A review of fault detection and diagnosis methodologies on air-handling units, Energy and Buildings 82: 550–562.
  • [29] Zhu, W., Zheng, Y., Dai, J. and Zhou, J. (2017). Design of integrated synergetic controller for the excitation and governing system of hydraulic generator unit, Engineering Applications of Artificial Intelligence 58: 79–87.
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-d1f87c9f-477f-4de0-a639-6ad078a32d2b
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