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State estimation-based distributed model predictive control of large-scale networked systems with communication delays

机译:具有通信延迟的基于状态估计的大型网络系统分布式模型预测控制

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摘要

In this paper, a cooperative distributed model predictive control is proposed for a class of large-scale systems composed of discrete-time linear subsystems which are coupled via states. The subsystems communicate with each other through a network with communication delays and they do not have direct access to their local states. In the proposed scheme, each subsystem is associated with a local MPC unit, a local predictor and a local observer. The local model predictive controllers exchange predicted input sequences via a delayed communication network. The local predictor uses the explicit model of the subsystems and predicts those states which are coupled between subsystems and their actual values are not available due to delays. The states of each subsystem are estimated from local measurements by designing a local observer. Convergence analysis of the proposed estimation methodology is performed and it is shown that the observer and predictor have exponential convergence. Furthermore, the exponential stability of the closed-loop system is existed. Finally, the theoretical results are verified by a simulation study.
机译:本文针对一类由状态耦合的离散线性子系统组成的大型系统,提出了一种协作式分布式模型预测控制。子系统之间通过通信延迟通过网络相互通信,它们不能直接访问其本地状态。在提出的方案中,每个子系统与一个本地MPC单元,一个本地预测器和一个本地观察者相关联。本地模型预测控制器通过延迟的通信网络交换预测的输入序列。局部预测器使用子系统的显式模型,并预测子系统之间耦合的状态,并且由于延迟而无法获得其实际值。通过设计本地观察者,可以从本地测量结果中估算每个子系统的状态。对所提出的估计方法进行了收敛性分析,结果表明观测器和预测器具有指数收敛性。此外,存在闭环系统的指数稳定性。最后,通过仿真研究验证了理论结果。

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