Degenerate Gradient Flows: A Comparison Study of Convergence Rate Estimates

dc.contributor.advisorKrishnaprasad, Perinkulam S.en_US
dc.contributor.authorAndersson, Sean B.en_US
dc.contributor.authorKrishnaprasad, Perinkulam S.en_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T10:12:17Z
dc.date.available2007-05-23T10:12:17Z
dc.date.issued2002en_US
dc.description.abstractDegenerate gradient flows arise in the context of adaptive control of linear systems when the usual gradient algorithm is used for the parameter update law. It is well known that in general parameter convergence is not guaranteed without further assumptions. The standard approach utilizes the notion of a persistently exciting input and different authors have derived different convergence rate estimates. In a recent paper Brockett re-examined this issue and developed a rate estimate using a property of symmetric matrices related to the condition number. In this paper we compare two well-known convergence rate estimates from the persistently exciting point of view with Brockett's estimate through a semianalytical numerical study. We establish a common footing by relating the assumptions of each theorem to the parameters specified under the persistently exciting condition. Our analysis shows that for all parameter values Anderson's result yields a tighter bound than the other two estimates. In each case the magnitude of the difference depends on the time it takes for the uniform observability condition to hold in the persistently exciting assumption. The shorter the time is, the larger the difference is.en_US
dc.format.extent169431 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/6283
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 2002-53en_US
dc.subjectSensor-Actuator Networksen_US
dc.titleDegenerate Gradient Flows: A Comparison Study of Convergence Rate Estimatesen_US
dc.typeTechnical Reporten_US

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