Numerical computations on feedback control and state estimation of the Kuramoto-Sivashinsky equation

Numerical computations are performed on linear and nonlinear feedback control and state estimation strategies for minimizing the fluctuations of the Kuramoto-Sivashinsky equation. The methodologies are based on the LQR/LQG theory and their extension to nonlinear problems. The optimal placements of s...

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Bibliographic Details
Main Authors: Lampayan, Valentine Blez L., Arellano, Christian Victor L., Lope, Jose Ernie C., del Rosario, Ricardo C.H.
Format: text
Published: Animo Repository 2009
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/7568
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Institution: De La Salle University
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Summary:Numerical computations are performed on linear and nonlinear feedback control and state estimation strategies for minimizing the fluctuations of the Kuramoto-Sivashinsky equation. The methodologies are based on the LQR/LQG theory and their extension to nonlinear problems. The optimal placements of sensors and actuators are first determined. The performance of the control and state estimation methods are then successfully tested using computer simulations. The obtained results indicate that the control and state estimation strategy both based only on the linear system is as good as the nonlinear methods implemented.