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Rolling self-triggered distributed MPC for dynamically coupled nonlinear systems☆
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DOI：10.1016/j.automatica.2023.111444.png)
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摘要
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The mutual influences caused by dynamic couplings in large-scale systems increase the difficulty in the design and analysis of distributed model predictive control (DMPC), and require information exchange among subsystems which calls for a scheduling strategy to save communication resources in communication-limited environments. To circumvent the two problems, we design a rolling self -triggered DMPC strategy for large-scale dynamically coupled systems with state and control input constraints. First, the optimal control problem where the cost is subject to the coupled dynamic and the constraints are subject to the uncoupled counterpart is proposed, forming the dual-model DMPC that is simple in design and analysis but yields good control performance. Second, the information exchange only occurs at some specified triggering instants determined by a rolling self-triggered mechanism, saving communication resources more significantly. The effectiveness of the designed strategy is verified by numerical simulations. (c) 2023 Published by Elsevier Ltd.
Keyword:
Dynamically coupled systems
Distributed model predictive control
Self -triggered control
Constrained nonlinear systems
期刊
IF:
5.9
论文数:
1.2W
被引数:
5.2W
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