Integrated Expert Control System for Intelligent Buildings
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
{'SignBlockName': 'Ken Chong', 'PO_EMAI': None, 'PO_PHON': None}
The object of this research is to investigate the feasibility of                applying artificial intelligence and advanced adaptive control                  techniques to building systems to develop an integrated expert                  control system for buildings.  This approach will have a                        hierarchical structure with two distinct features, namely a                     foreground/background optimization scheme which handles dynamics                of the building system with time constants of different orders                  of magnitude; and a hybrid algorithmic/rule-based decision-making               scheme.  The background supervisory controller utilizes the detailed            building system models to make decisions regarding the slow dynamics and        disturbances of the order of days, while the foreground control schemes         tune the HVAC equipment and lighting system to compensate for fast              dynamics, such as occupancy variations.  The significant features of            this research include:  (1) development of a three-level hierarchical           intelligent control scheme, which compensates for system and                    environmental uncertainties;  (2) formulation of a performance                  index for global optimization of a building system with emphasis                on energy management, occupant comfort and operating and                        maintenance costs;  (3) formulation and implementation of HVAC                  equipment self-tuning local controllers with set points determined by           the second level controller;  (4) formulation and implementation of an          on-line diagnostic scheme which utilizes sensory information to                 calculate instantaneous statistical characteristics of the system for           real-time failure detection and failed component isolation;  (5)                formulation of an algorithmic decision-making scheme based on the               minimum uncertainty (entropy) concept.  The resulting techniques will be        simulated and to some extent implemented on small scale subsystem of a          building.  Industrial cooperation will be sought to plan implementation         of the results on an actual building after the two-year duration of this        study.
[{'FirstName': 'Rahmatallah', 'LastName': 'Shoureshi', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rahmatallah A Shoureshi', 'EmailAddress': 'rshoures@du.edu', 'NSF_ID': '000106285', 'StartDate': '01/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Richard', 'LastName': 'Walker', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Richard Walker', 'EmailAddress': None, 'NSF_ID': '000282111', 'StartDate': '01/01/1988', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
{'Name': 'Purdue Research Foundation', 'CityName': 'WEST LAFAYETTE', 'ZipCode': '479064353', 'PhoneNumber': '3174946200', 'StreetAddress': '1281 WIN HENTSCHEL BLVD STE 2500', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Indiana', 'StateCode': 'IN', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'IN04', 'ORG_UEI_NUM': 'C1G1LGYJF5G5', 'ORG_LGL_BUS_NAME': 'PURDUE RESEARCH FOUNDATION', 'ORG_PRNT_UEI_NUM': 'YRXVL4JYCEF5'}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '1442', 'Text': 'CONSTRUCTION AND INFRASTRUCTUR'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8718863.xml'}