Abstract
Heating, ventilation and air-conditioning (HVAC) system is an important component of Smart Home. The HVAC system is connected to network for the transfer of measurement data and control action packets from sensors to controller and controller to actuators respectively. The HVAC system can therefore be categorized as a Cyber-Physical system (CPS). Such systems are prone to communication uncertainties like packet losses and delays. Such systems require integrated architecture of communication and control. An evolutionary algorithm tuned fuzzy PI controller design coupled in a communication framework is presented in this paper for performance improvements of HVAC system. The entire architecture considers relevant system objectives based on system states and actuator actions. The formulated problem has been solved through real time optimization approach using the designed controller following the communication protocol. The developed algorithm helps in obtaining optimal actuator actions and shows a fast convergence to the different desired temperature sets. The results also show that the system can recover from sudden burst packet losses.
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References
L. Mingfu, L.H. Ju, Design and implementation of smart home control system based on wireless sensor networks and power line communications. IEEE Trans. Ind. Electron. 62(7), 4430–4442 (2015)
A. Zanella, N. Bui, A. Castellani, L. Vangelista, M. Zorzi, Internet of things for smart cities. IEEE Internet Things J. 1(1), 22–32 (2014)
J. Sztipanovits, G. Karsai, P. Antsaklis, J. Baras, Toward a science of cyber-physical system integration. Proc. IEEE 100(1), 29–44 (2012)
W. Zhang, M.S. Branicky, S.M. Pjillips, Stability of networked control systems. IEEE Control Syst. Mag. 1, 84–99 (2001)
B. Sun, P.B. Luh, Q.S. Jia, Z. O’Neill, F. Song, Building energy doctors: an SPC and Kalman filter-based method for system-level fault detection in HVAC systems. IEEE Trans. Auto. Sci. and Eng. 11(1), 215–229 (2014)
M.B.G. Cloosterman, N.D. Wouw, W.P.M.H. Heemels, H. Nijmeijer, Stability of networked control systems with uncertain time-varying delays. IEEE Trans. Auto. Control 54(7), 1575–1580 (2009)
M. Nourian, A.S. Leong, S. Dey, D.E. Quevedo, An optimal transmission strategy for Kalman filtering over packet dropping links with imperfect acknowledgements. IEEE Trans. Control Netw. Syst. 1(3), 259–271 (2014)
M. Anderson, M. Buehner, P. Young, D. Hittle, C. Anderson, J. Tu, D. Hodgson, MIMO robust control for HVAC systems. IEEE Trans. Control Syst. Tech. 16(3), 475–483 (2008)
P.I.-H. Lin, H.L. Broberg, Internet-based monitoring and controls for HVAC applications. IEEE Ind. Appl. Mag. 8(1), 49–54 (2002)
V. Reppa, P. Papadopouos, M.M. Polycarpou, C.G. Panayiotou, A distibuted architecture for HVAC sensor fault detection and isolation. IEEE Trans. Control Syst. Tech. 23(4), 1323–1337 (2015)
X. Cao, P. Cheng, J. Chen, Y. Sun, An online optimization approach for control and communication codesign in networked cyber-physical systems. IEEE Trans. Ind. Inf. 9(1), 439–450 (2013)
A. Chiuso, N. Laurenti, L. Schenato, A. Zanella, LQG cheap control over SNR-limited lossy channels with delay, in IEEE 52nd Annual Conference on Decision and Control (CDC) (2013), pp. 3988–3993
S. Dey, A. Chiuso, L. Schenato, Remote estimation with noisy measurments subject to packet loss and quantization noise. IEEE Trans. Control Netw. Syst. 1(3), 204–217 (2014)
H. Li, M.Y. Chow, Z. Sun, Optimal stabilizing gain selection for networked control systems with time delays and packet losses. IEEE Trans. Control Syst. Tech. 17(5), 1154–1162 (2009)
Z.H. Pang, G.P. Liu, D. Zhou, M. Chen, Output tracking control for networked systems: a model-based prediction approach. IEEE Trans. Ind. Electron. 61(9), 4867–4877 (2014)
L. Schenato, B. Sinopoli, M. Franceschetti, K. Poola, S.S. Sastry, Foundations of control and estimation over lossy networks. Proc. IEEE 95(1), 1693–1698 (2007)
X. Cao, J. Chen, C. Gao, Y. Sun, An optimal control method over wireless sensor/actuator networks. Comput. Electr. Eng. 35(5), 748–756 (2009)
J. Bai, X. Zhang, A new adaptive PI controller and its application in HVAC systems. Energy Convers. Manage. (ScienceDirect) 49, 1043–1054 (2007)
N.K. Verma, M. Hanmandlu, From a Gaussian mixture model to nonadditive fuzzy systems. IEEE Trans. Fuzzy Syst. 15(5), 809–826 (2007)
H.H. Choi, H.M. Yun, Y. Kim, Implementation of evolutionary fuzzy PID speed controller for PM synchronous motor. IEEE Trans. Ind. Inf. 11(2), 540–547 (2015)
G. Ye, C. Yang, Y. Chen, Y. Li, A new approach for measuring predicted mean vote (PMV) and standaard effective temperature (SET). Build. Environ. 38(1), 33–44 (2003)
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Dhar, N.K., Verma, N.K., Behera, L. (2018). Evolutionary Algorithm Tuned Fuzzy PI Controller for a Networked HVAC System. In: Zadeh, L., Yager, R., Shahbazova, S., Reformat, M., Kreinovich, V. (eds) Recent Developments and the New Direction in Soft-Computing Foundations and Applications. Studies in Fuzziness and Soft Computing, vol 361. Springer, Cham. https://doi.org/10.1007/978-3-319-75408-6_25
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DOI: https://doi.org/10.1007/978-3-319-75408-6_25
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