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Self-Triggered Model Predictive Control for Nonlinear Input-Affine Dynamical Systems via Adaptive Control Samples Selection.
- Source :
-
IEEE Transactions on Automatic Control . Jan2017, Vol. 62 Issue 1, p177-189. 13p. - Publication Year :
- 2017
-
Abstract
- In this paper, we propose a self-triggered formulation of model predictive control for continuous-time nonlinear input-affine networked control systems. Our control method specifies not only when to execute control tasks but also provides a way to discretize the optimal control trajectory into several control samples, so that the reduction of communication load will be obtained. Stability analysis under the sample-and-hold implementation is also given, which guarantees that the state converges to a terminal region where the system can be stabilized by a local state feedback controller. Some simulation examples validate our proposed framework. [ABSTRACT FROM PUBLISHER]
Details
- Language :
- English
- ISSN :
- 00189286
- Volume :
- 62
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Automatic Control
- Publication Type :
- Periodical
- Accession number :
- 120459056
- Full Text :
- https://doi.org/10.1109/TAC.2016.2537741