IUC: Adaptive Control of Non-Linear Sampled-Data Systems
{'Code': '07010000', 'Directorate': {'LongName': 'Directorate For Engineering'}, 'Division': {'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
{'SignBlockName': 'Kristen M. Biggar, N-BioS'}
This research concerns the study of adaptive control of sampled-data systems which contain at least one non-linearity. The motivation for the study is to bring the theory of adaptive control closer to the reality of practical problems. The method of study proposed is to combine the small gain theory with the method of averaging in the environment of equations written in error space. The method uses the idea of a tuned system as introduced recently by Kosut. The class of sampled-data systems to be studied includes virtually every successful application of adaptive control known. Inclusion of some non-linearity in the plant to be controlled completes the consideration of non-ideal process already begun in many studies by consideration of un-modelled dynamics, bounded disturbances and sensor noise.
{'FirstName': 'Robert', 'LastName': 'Kosut', 'EmailAddress': 'kosut@scsolutions.com', 'StartDate': '04/15/1986', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Integrated Systems Inc', 'CityName': 'Sunnyvale', 'ZipCode': '940891322', 'PhoneNumber': '4085421816', 'StreetAddress': '201 Moffett Park Drive', 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1986&All=true', 'xml': '8605646.xml'}