Self-triggered robust model predictive control for nonlinear systems with bounded disturbances
A self-triggered model predictive control (MPC) scheme for continuous-time perturbed nonlinear systems subject to bounded disturbances is investigated in this study. A self-triggered strategy is designed to obtain the inter-execution time before the next trigger using the current sampled state. An o...
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| Vydáno v: | IET control theory & applications Ročník 13; číslo 9; s. 1336 - 1343 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
The Institution of Engineering and Technology
11.06.2019
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| Témata: | |
| ISSN: | 1751-8644, 1751-8652 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | A self-triggered model predictive control (MPC) scheme for continuous-time perturbed nonlinear systems subject to bounded disturbances is investigated in this study. A self-triggered strategy is designed to obtain the inter-execution time before the next trigger using the current sampled state. An optimisation problem is addressed to obtain the optimal control trajectory at each triggered instant. The so-called dual-mode approach is used to stabilise the perturbed closed-loop system. Furthermore, sufficient conditions are derived to ensure the feasibility and stability, respectively. It is shown that with a properly designed prediction horizon, the feasibility of the proposed self-triggered MPC algorithm can be guaranteed if the disturbance is bounded in a small enough area. Meanwhile, the stability is proved under the self-triggered condition. Finally, a numerical example is given to illustrate the efficacy of the authors proposed scheme. |
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| ISSN: | 1751-8644 1751-8652 |
| DOI: | 10.1049/iet-cta.2018.5459 |