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Automated reasoning techniques for i...

Brackney, Larry J.

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Automated reasoning techniques for intelligent control of building systems.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Automated reasoning techniques for intelligent control of building systems./
Author:	Brackney, Larry J.
Description:	169 p.
Notes:	Source: Dissertation Abstracts International, Volume: 56-02, Section: B, page: 1046.
Contained By:	Dissertation Abstracts International56-02B.
Subject:	Engineering, Mechanical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9523317

Automated reasoning techniques for intelligent control of building systems.
Brackney, Larry J.

Automated reasoning techniques for intelligent control of building systems. - 169 p.

Source: Dissertation Abstracts International, Volume: 56-02, Section: B, page: 1046.

Thesis (Ph.D.)--Purdue University, 1994.

A self-organizing controller based on fuzzy set theory is applied to the problem of building temperature and lighting control. A three-level hierarchical control structure composed of supervisor, coordinator, and local layers is employed.Subjects--Topical Terms:

783786
Engineering, Mechanical.

Automated reasoning techniques for intelligent control of building systems.
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035 $a (UnM)AAI9523317
035 $a AAI9523317
040 $a UnM $c UnM
100 1 $a Brackney, Larry J. $3 1952251
245 1 0 $a Automated reasoning techniques for intelligent control of building systems.
300 $a 169 p.
500 $a Source: Dissertation Abstracts International, Volume: 56-02, Section: B, page: 1046.
500 $a Major Professor: Rahmat Shoureshi.
502 $a Thesis (Ph.D.)--Purdue University, 1994.
520 $a A self-organizing controller based on fuzzy set theory is applied to the problem of building temperature and lighting control. A three-level hierarchical control structure composed of supervisor, coordinator, and local layers is employed.
520 $a Fuzzy sets representing zone occupancy, utility cost, and building dynamics are used along with weather forecast data as inputs to the supervisor, which generates local controller setpoint schedules based on accumulated knowledge of past building usage and behavior. The supervisor is autonomously optimized with respect to a performance index penalizing energy consumption, occupant discomfort, and fuzzy model error.
520 $a The coordinator layer of the intelligent building system is responsible for short term error correction, and modifies the supervisor schedule when unexpected occupancies occur. Both lighting and temperature setpoints may be changed to maintain occupant comfort using a fuzzy rule-base, which relates setpoint errors with the appropriate corrections.
520 $a Implementation of the system in an office building results in a 20 to 40% savings in energy as compared to a constant setpoint scheme. Improvement over traditional night setback schedules is also expected, as the controller is designed to accommodate variable occupancy loading conditions. The ability of the HVAC system to meet heating or cooling demand may also be enhanced since the intelligent building control system may dynamically shed load from unoccupied zones.
590 $a School code: 0183.
650 4 $a Engineering, Mechanical. $3 783786
650 4 $a Engineering, System Science. $3 1018128
690 $a 0548
690 $a 0790
710 2 0 $a Purdue University. $3 1017663
773 0 $t Dissertation Abstracts International $g 56-02B.
790 1 0 $a Shoureshi, Rahmat, $e advisor
790 $a 0183
791 $a Ph.D.
792 $a 1994
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9523317