Abstract
A formulation of continuous-time nonlinear MPC is proposed in which input trajectories are described by general time-varying parameterizations. The approach entails a limiting case of suboptimal single-shooting, in which the dynamics of the associated NLP are allowed to evolve within the same timescale as the process dynamics, resulting in a unique type of continuous-time dynamic state feedback which is proven to preserve stability and feasibility.
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Keywords
- Model Predictive Control
- Prediction Horizon
- Hybrid Automaton
- Nonlinear Model Predictive Control
- Base Model Predictive Control
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DeHaan, D., Guay, M. (2007). A New Real-Time Method for Nonlinear Model Predictive Control. 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_45
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DOI: https://doi.org/10.1007/978-3-540-72699-9_45
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