Model Reference Adaptive Control with Input and Output      Constraints
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
{'SignBlockName': 'Radhakisan Baheti', 'PO_EMAI': None, 'PO_PHON': None}
The goal of the proposed research is to design, analyze and implement           a model reference adaptive control algorithm with constraints on the            amplitude and the rate of change of input and output signals.  The              robustness of the proposed algorithm with respect to bounded                    disturbance and time-varying parameters will be considered.                                                                                                     Much work has been done in the development of highly sophisticated              adaptive algorithms.  The existing results, however, largely ignore             the presence of realistic input and output constraints.  So far the             stability results have been established for adaptive control                    algorithms with saturating inputs and open-loop stable plants.                                                                                                  In this work a model reference adaptive control algorithm is proposed           with time-varying reference model, time-varying regulation dynamics             and long-range prediction principle.  Using this method the saturation          of the input and output signals, which can lead to instability, is to           a large extent avoided.  The aim is to obtain good tracking and                 regulation properties satisfying at the same time prespecified input            and output constraints.                                                                                                                                         The developed algorithm will be analyzed and extensively checked by             simulations for both stable and unstable open-loop plants.  It will be          finally applied for control of blood pressure in human body and for             control of robotic manipulators.
{'FirstName': 'Grazyna', 'LastName': 'Pajunen', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Grazyna A Pajunen', 'EmailAddress': 'pajuneng@fau.edu.', 'NSF_ID': '000482477', 'StartDate': '09/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Florida Atlantic University', 'CityName': 'BOCA RATON', 'ZipCode': '334316424', 'PhoneNumber': '5612970777', 'StreetAddress': '777 GLADES RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '23', 'CONGRESS_DISTRICT_ORG': 'FL23', 'ORG_UEI_NUM': 'Q266L2NDAVP1', 'ORG_LGL_BUS_NAME': 'FLORIDA ATLANTIC UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '145400', 'Text': 'SYSTEMS THEORY'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8809749.xml'}