Comfort control in residential housing using predictive controllers

被引:3
|
作者
Dumur, D
Boucher, P
Murphy, KM
Deque, F
机构
关键词
predictive control; climate control; process control; modelling;
D O I
10.1109/CCA.1997.627552
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Generalised Predictive Control (GPC) has shown to be an effective strategy for high performance applications, with good temporal and frequency properties (small overshoot, cancellation of disturbances, good stability and robustness margins). This paper presents an application of GPC to climate control in buildings, with particular attention focused on achieving strict temperature setpoint specifications. Specifically, the future temperature setpoint (step like in nature) is prespecified or known and the objective is to attain leading edge temperatures (positive increase) to within +/- 0.5 degrees C at the specified time. In addition, the controller must regulate the temperature to within +/- 0.5 degrees C through out the entire duration of the setpoint pulse and turn off the heater coincident with the trailing edge of the step change. In this paper, a new approach using GPC is developed for use in the comfort control problem. The final controller consists of a standard RST regulator derived from GPC and the development of an empirical anticipative rule which shifts the future setpoint backward in time in order to launch the heater sufficiently in the past to attain the leading edge setpoint value. An important result is that this new regulator is in operation continuously which is initialized only at start up. That is, no switching in or out of controllers is needed as is the case when PI with bang-bang is used. The validity and workability of such a predictive structure for thermal control in buildings is finally pointed out with the results of the predictive controller in the CLIM2000 environment, coupled with an automatic design of the tuning parameters for a simplified implementation.
引用
收藏
页码:265 / 270
页数:6
相关论文
共 50 条
  • [31] Energy savings and guaranteed thermal comfort in hotel rooms through nonlinear model predictive controllers
    Acosta, Adriana
    Gonzalez, Ana I.
    Zamarreno, Jesus M.
    Alvarez, Victor
    ENERGY AND BUILDINGS, 2016, 129 : 59 - 68
  • [32] A thermal comfort-driven model predictive controller for residential split air conditioner
    Pandey, Brijesh
    Bohara, Bharat
    Pungaliya, Rajat
    Patwardhan, Sachin C.
    Banerjee, Rangan
    JOURNAL OF BUILDING ENGINEERING, 2021, 42
  • [33] Thermal comfort-conscious eco-climate control for electric vehicles using model predictive control
    Kwak, Kyoung Hyun
    Chen, Youyi
    Kim, Jaewoong
    Kim, Youngki
    Jung, Dewey D.
    CONTROL ENGINEERING PRACTICE, 2023, 136
  • [34] New control model for autonomous vehicles using integration of Model Predictive and Stanley based controllers
    Al-Jumaili, Mustafa Hamid
    Ozok, Yasa Eksioglu
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [35] Boiler combustion control using the intelligent controllers Boiler combustion control using the intelligent controllers
    Du, Yunhe
    Xing, Jianchun
    Wang, Ping
    Wang, Shuangqing
    Yang, Qiliang
    TENCON 2005 - 2005 IEEE REGION 10 CONFERENCE, VOLS 1-5, 2006, : 1959 - +
  • [36] Model Predictive Control of Residential Demand in Low Voltage Network using Ice Storage
    Jazaeri, Javad
    Alpcan, Tansu
    Gordon, Robert L.
    2018 AUSTRALIAN & NEW ZEALAND CONTROL CONFERENCE (ANZCC), 2018, : 51 - 55
  • [37] A survey of grinding circuit control methods:: from decentralized PID controllers to multivariable predictive controllers
    Pomerleau, A
    Hodouin, D
    Desbiens, A
    Gagnon, É
    POWDER TECHNOLOGY, 2000, 108 (2-3) : 103 - 115
  • [38] Co-design of predictive controllers for wireless network control
    Irwin, G. W.
    Chen, J.
    McKernan, A.
    Scanlon, W. G.
    IET CONTROL THEORY AND APPLICATIONS, 2010, 4 (02): : 186 - 196
  • [39] Tuning Generalized Predictive PI controllers for process control applications
    Briones, Oscar
    Alarcon, Ruben
    Rojas, Alejandro J.
    Sbarbaro, Daniel
    ISA TRANSACTIONS, 2022, 119 : 184 - 195
  • [40] Survey of grinding circuit control methods: From decentralized PID controllers to multivariable predictive controllers
    Pomerleau, Andre
    Hodouin, Daniel
    Desbiens, Andre
    Gagnon, Eric
    Powder Technology, 2000, 108 (02) : 103 - 115