Abstract
We provide a theoretical framework for model predictive control of infinite-dimensional systems, like, e.g., nonlinear parabolic PDEs, including stochastic disturbances of the input signal, the output measurements, as well as initial states. The necessary theory for implementing the MPC step based on an LQG design for infinite-dimensional linear time-invariant systems is presented. We also briefly discuss the necessary ingredients for the numerical computations using the derived theory.
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Keywords
- Riccati Equation
- Model Predictive Control
- Burger Equation
- Nonlinear Model Predictive Control
- Local Optimization Problem
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Benner, P., Hein, S. (2013). MPC/LQG for Infinite-Dimensional Systems Using Time-Invariant Linearizations. In: Hömberg, D., Tröltzsch, F. (eds) System Modeling and Optimization. CSMO 2011. IFIP Advances in Information and Communication Technology, vol 391. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36062-6_22
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DOI: https://doi.org/10.1007/978-3-642-36062-6_22
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