PYI: Nonlinear Control and Order Reduction
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
{'SignBlockName': 'Arthur R. Bergen', 'PO_EMAI': None, 'PO_PHON': None}
This PYI award will fund research into the development of a             methodology for order reduction of nonlinear systems which (i) respects         and preserves the nonlinearity of the original model, (ii) does not             require exact knowledge of the relative speeds of various system                variables, and (iii) incorporates the effect of an exogenous control            input.  The results will have implications for nonlinear controller             design of systems with fast and slow modes.  There are two major reasons        for developing a nonlinear model order reduction technique.  The first          is common to all large dynamical engineering systems:  the large number         of governing equations.  The second reason concerns the fact that               nonlinear effects can not be neglected since they will often be the             deciding influence in the performance of many advanced engineering              systems, such as high-performance aircraft, rapidly maneuvering                 spacecraft, and chemical reactors.  Only the first of these issues is           considered in the standard technique of first linearizing the dynamical         equations and then using a linear model order reduction technique.              Clearly, any nonlinear effect (such as bifurcations, or even nonlinear          transient response) will be lost using this approach.  The main                 analytical framework for this study consists of multiparameter singular         perturbation theory and center manifold theory.  These two powerful             tools will be merged and extended. Use of functional-analytic results           such as the so-called hard implicit function theorem will be made.   The        research supported under this PYI award concerns the                            development of a methodology for model order reduction of nonlinear             systems.  The approach will attempt to preserve the nonlinear nature of         the original system since the nonlinearities may be the deciding                influence in many advanced engineering systems.
{'FirstName': 'Eyad', 'LastName': 'Abed', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Eyad H Abed', 'EmailAddress': 'abed@umd.edu', 'NSF_ID': '000276375', 'StartDate': '07/01/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'ZipCode': '207425100', 'PhoneNumber': '3014056269', 'StreetAddress': '3112 LEE BUILDING', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MD04', 'ORG_UEI_NUM': 'NPU8ULVAAS23', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MARYLAND, COLLEGE PARK', 'ORG_PRNT_UEI_NUM': 'NPU8ULVAAS23'}
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[{'Code': '1454', 'Text': 'SYSTEMS THEORY'}, {'Code': '1518', 'Text': 'CONTROL, NETWORKS, & COMP INTE'}]
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1986&All=true', 'xml': '8657561.xml'}