Kuramoto-Sivashinsky dynamics on the center-unstable manifold
SIAM Journal on Applied Mathematics
Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Back in the saddle again: a computer assisted study of the Kuramoto-Sivashinsky equation
SIAM Journal on Applied Mathematics
An approximate inertial manifold for computing Burgers' equation
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
A remark on quasi-stationary approximate inertial manifolds for the Navier-Stokes equations
SIAM Journal on Mathematical Analysis
Postprocessing the Galerkin Method: a Novel Approach to Approximate Inertial Manifolds
SIAM Journal on Numerical Analysis
Control of the Burgers equation by a reduced-order approach using proper orthogonal decomposition
Journal of Optimization Theory and Applications
Feedback control methodologies for nonlinear systems
Journal of Optimization Theory and Applications
Modeling and control of physical processes using proper orthogonal decomposition
Mathematical and Computer Modelling: An International Journal
Using adaptive proper orthogonal decomposition to solve the reaction--diffusion equation
Applied Numerical Mathematics
Optimal boundary control of Kuramoto-Sivashinsky equation
ACC'09 Proceedings of the 2009 conference on American Control Conference
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In this paper, we consider the Kuramoto-Sivashinsky equation (KSE), which describes the long-wave motions of a thin film over a vertical plane. Solution procedures for the KSE often yield a large or infinite-dimensional nonlinear system. We first discuss two reduced-order methods, the approximate inertial manifold and the proper orthogonal decomposition, and show that these methods can be used to obtain a reduced-order system that can accurately describe the dynamics of the KSE. Moreover, from this resulting reduced-order system, the feedback controller can readily be designed and synthesized. For our control techniques, we use the linear and nonlinear quadratic regulator methods, which are the first- and second-order approximated solutions of the Hamilton-Jacobi-Bellman equation, respectively. Numerical simulations comparing the performance of the reduced-order-based linear and nonlinear controllers are presented.