Abstract
In this work, we propose a computationally efficient method for the solution of dynamic constraint optimization problems arising in the context of spatially-distributed processes governed by highly-dissipative non-linear partial differential equations (PDEs). The method is based on spatial discretization using combination of the method of weighted residuals with spatially-global basis functions and approximate inertial manifolds. We use the Kuramoto-Sivashinsky equation, a model that describes incipient instabilities in a variety of physical and chemical systems, to demonstrate the implementation and evaluate the effectiveness of the proposed optimization method.
Original language | English (US) |
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Pages (from-to) | 2310-2316 |
Number of pages | 7 |
Journal | Proceedings of the IEEE Conference on Decision and Control |
Volume | 2 |
State | Published - 2002 |
Event | 41st IEEE Conference on Decision and Control - Las Vegas, NV, United States Duration: Dec 10 2002 → Dec 13 2002 |
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Modeling and Simulation
- Control and Optimization