Abstract
The topic of this paper is a new model predictive control (MPC) approach for the sampled-data implementation of continuous-time stabilizing feedback laws. The given continuous-time feedback controller is used to generate a reference trajectory which we track numerically using a sampled-data controller via an MPC strategy. Here our goal is to minimize the mismatch between the reference solution and the trajectory under control. We summarize the necessary theoretical results, discuss several aspects of the numerical implemenation and illustrate the algorithm by an example.
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Keywords
- Optimal Control Problem
- Model Predictive Control
- Time Feedback
- Recede Horizon Control
- Good Initial Guess
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Grüne, L., Nešić, D., Pannek, J. (2007). Model Predictive Control for Nonlinear Sampled-Data Systems. In: Findeisen, R., Allgöwer, F., Biegler, L.T. (eds) Assessment and Future Directions of Nonlinear Model Predictive Control. Lecture Notes in Control and Information Sciences, vol 358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72699-9_8
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DOI: https://doi.org/10.1007/978-3-540-72699-9_8
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