Title :
Estimating the inputs of gas transport processes in buildings
Author :
Federspiel, Clifford C.
Author_Institution :
Johnson Controls Inc., Milwaukee, WI, USA
fDate :
9/1/1997 12:00:00 AM
Abstract :
Information about the strength of gas sources in buildings has a number of applications in the area of building automation and control, including temperature and ventilation control, fire detection, and security systems. In this paper, a method for estimating the strength of a gas source in an enclosure when some of the parameters of the gas transport process are unknown is described. It is based on a perfect-mixing model of the gas species transport dynamics. The estimation problem is formulated as a Kalman filtering problem, where the states estimated by the Kalman filter are the unknown process parameters and the source strength. Sudden changes in the strength of the source are detected and tracked with a hypothesis testing and covariance resetting algorithm that is based on statistics provided by the Kalman filter. Experimental results from two first-order systems demonstrate the efficacy of this method
Keywords :
Kalman filters; building management systems; chemical variables measurement; discrete time systems; filtering theory; gas mixtures; gas sensors; parameter estimation; security; state estimation; statistical analysis; temperature control; transport processes; ventilation; Kalman filtering problem; building automation; buildings; covariance resetting algorithm; fire detection; first-order systems; gas sources; gas transport processes; hypothesis testing; perfect-mixing model; security systems; temperature control; transport dynamics; ventilation control; Automatic control; Automation; Control systems; Filtering; Fires; Information security; Kalman filters; State estimation; Temperature control; Ventilation;
Journal_Title :
Control Systems Technology, IEEE Transactions on
