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Indirect adaptive control using the linear quadratic solution

This thesis studies the indirect adaptive control for discrete linear time invariant systems. The adaptive control strategy is based on the linear quadratic regulator that places the closed loop poles such that an infinite stage quadratic cost function is minimized. The plant parameters are identified recursively using a projection algorithm. / First, we study the effect of the model over-parametrization. For this purpose, we introduce an algorithm to generate the controller parameters recursively. This asymptotic reformulation is shown to overcome situations in which the pole-zero cancellation is a limit point of the identification algorithm. We also show that the algorithm will generate a unique control sequence that converges asymptotically to the solution of the Diophantine (pole assignment) equation. / Next, we study the stability of the proposed adaptive scheme in both deterministic and stochastic cases. We show that the global stability of the resulting adaptive scheme is obtained with no implicit assumptions about parameter convergence or the nature of the external input. Then the global convergence of the adaptive algorithm is obtained if the external input is "persistently exciting". By convergence we mean that the adaptive control will converge to the optimal control of the system. / The performance of the adaptive algorithm in the presence of deterministic disturbances is also considered, where we show that the adaptive controller performs relatively well if the model order is high enough to include a description of the disturbances.

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.72028
Date January 1985
CreatorsGhoneim, Youssef Ahmed.
PublisherMcGill University
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
LanguageEnglish
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Formatapplication/pdf
CoverageDoctor of Philosophy (Department of Electrical Engineering.)
RightsAll items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated.
Relationalephsysno: 000226653, proquestno: AAINL24022, Theses scanned by UMI/ProQuest.

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