Pattern Recognition and Feedback via Parallel Distributed   Computation
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
{'SignBlockName': 'Maria Burka', 'PO_EMAI': None, 'PO_PHON': None}
The purpose of this project is to determine the feasibility of                  applying the Parallel Distributed Processing (PDP) approach to on-line          feedback control of nonlinear chemical processes.  PDP theory assumes           that many complex processes in cognition can be represented by a large          set of individually simple interconnected units with complex                    interactions.  Parallel refers to the fact that units excite and                inhibit each other simultaneously in the network while distributed              indicates that knowledge consists of connection strengths between               pairs of units that are distributed throughout the network.  This               approach "learns" as it goes along, i.e. it is a technique that mimics          human intelligence gathering.                                                                                                                                   Adaptive controllers work by changing in response to process changes.           This is feasible for linear systems but much more complex for                   nonlinear systems.  In this research project, the PDP network model             will be used for the development of sensitivities and local                     linearizations that can be used for controller design for nonlinear             chemical processes.                                                                                                                                             The PI plans experimental verification of the algorithms developed on           a laboratory methanol distillation column.  This will permit                    comparisons with self-turning and other adaptive controllers.
{'FirstName': 'Erik', 'LastName': 'Ydstie', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Erik Ydstie', 'EmailAddress': 'ydstie@cmu.edu', 'NSF_ID': '000106340', 'StartDate': '02/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Massachusetts Amherst', 'CityName': 'AMHERST', 'ZipCode': '010039252', 'PhoneNumber': '4135450698', 'StreetAddress': '101 COMMONWEALTH AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'MA02', 'ORG_UEI_NUM': 'VGJHK59NMPK9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MASSACHUSETTS', 'ORG_PRNT_UEI_NUM': 'VGJHK59NMPK9'}
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{'Code': '1403', 'Text': 'Proc Sys, Reac Eng & Mol Therm'}
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