On using LQG performance metrics for sensor placement

Author

Borggaard, J. ; Burns, J. ; Zietsman, L.

Author_Institution

Dept. of Math., Virginia Tech, Blacksburg, VA, USA

fYear

2011

fDate

June 29 2011-July 1 2011

Firstpage

2381

Lastpage

2386

Abstract

We discuss four metrics for determining sensor placement in energy efficient building design. These include the norm of the observer gain, the trace of the observer Riccati solution, the distance to the nearest unobservable system, and the linear quadratic Gaussian (LQG) cost from given initial state and state estimates. These metrics have different computational complexity, but all lead to the same optimal sensor location in this study where a single room model is considered.

Keywords

HVAC; Riccati equations; building management systems; cost optimal control; distributed parameter systems; linear quadratic Gaussian control; observability; observers; performance index; temperature control; temperature sensors; HVAC system; LQG performance metrics; average temperature control; computational complexity; distributed parameter control theory; energy efficient building design; linear quadratic Gaussian cost; nearest unobservable system; observer Riccati solution; observer gain; optimal sensor location; sensor placement; single room model; state estimate; temperature sensor; Computational modeling; Control systems; Equations; Mathematical model; Measurement; Observers; Temperature sensors;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference (ACC), 2011

Conference_Location

San Francisco, CA

ISSN

0743-1619

Print_ISBN

978-1-4577-0080-4

Type

conf

DOI

10.1109/ACC.2011.5991462

Filename

5991462