Self-triggered model predictive control for nonlinear continuous-time networked system via ensured performance control samples selection
Author:
Affiliation:
1. School of Mathematical Sciences, Tongji University, Shanghai, People's Republic of China
2. School of Mathematics and Computer Science, Zhejiang Normal University, Jinhua, People's Republic of China
Funder
NNSF of China
Publisher
Informa UK Limited
Subject
Computer Science Applications,Control and Systems Engineering
Link
https://www.tandfonline.com/doi/pdf/10.1080/00207179.2021.1936189
Reference33 articles.
1. Robust MPC suitable for closed-loop re-identification, based on probabilistic invariant sets
2. To Sample or not to Sample: Self-Triggered Control for Nonlinear Systems
3. Robust self-triggered model predictive control for constrained discrete-time LTI systems based on homothetic tubes
4. Robust self-triggered MPC for constrained linear systems: A tube-based approach
5. Communication Scheduling in Robust Self-Triggered MPC for Linear Discrete-Time Systems∗∗The authors would like to thank the German Research Foundation (DFG) for financial support of the project within the Cluster of Excellence in Simulation Technology (EXC 310/2) at the University of Stuttgart. The authors would also like to thank the DFG for their financial support within the research grant AL 316/9-1. This work is also supported by the Innovational Research Incentives Scheme under the VICI grant Wireless control systems: A new frontier in automation” (no. 11382) awarded by NWO (Netherlands Organization for Scientific Research) and STW (Dutch Science Foundation). Corresponding author F. D. Brunner.
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1. An integral‐differential combined type event‐triggered model predictive control for perturbed linear systems;Asian Journal of Control;2023-02-16
2. Self-Triggered Model Predictive Control With Sample-and-Hold Fashion for Constrained Continuous-Time Linear Systems;Journal of Dynamic Systems, Measurement, and Control;2023-01-11
3. Engineering Emergence: A Survey on Control in the World of Complex Networks;Automation;2022-03-10
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