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Title:Optimal adaptive control with ΘLQG
Author(s):Wendt, Luke
Advisor(s):Levinson, Stephen E.
Department / Program:Electrical & Computer Eng
Discipline:Electrical & Computer Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Optimal Adaptive Control
Multiple-Input Multiple-Output (MIMO)
Extended Kalman Filter (EKF)
Hyper-Extended Kalman Filter (EKF)
Linear Quadratic Regulator (LQR)
Linear Quadratic Gaussian Regulator (LQG)
Hyper Extended LQG (ΘLQG)
Pendulum on Cart
Abstract:This thesis introduces ΘLQG, the hyper extension of the Linear Quadratic Gaussian Regulator, for solving general purpose (locally optimal) nonlinear adaptive control on multiple-input multiple-output systems. This approach can be used to stabilize an under-actuated under-observed nonlinear dynamic system with noisy measurements while simultaneously identifying system parameters. It requires a parameterized dynamic model with operation about equilibrium points. Its general construction can also be used in disturbance rejection, gain scheduling and reference tracking. Specific case examples are introduced.
Issue Date:2013-05-24
Rights Information:Copyright 2013 Luke Adam Wendt
Date Available in IDEALS:2013-05-24
Date Deposited:2013-05

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