Director of Research (if dissertation) or Advisor (if thesis)
Levinson, Stephen E.
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(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.
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