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Robust distributed model predictive control for uncertain networked control systems

机译:不确定网络控制系统的鲁棒分布模型预测控制

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摘要

In this study, an approach to design robust distributed model predictive control (MPC) is proposed for polytopic uncertain networked control systems with time delays. To reduce the computational complexity and improve the flexibility, the entire system is decomposed into multiple smaller dimensional subsystems. For each subsystem, the proposed robust distributed MPC algorithm requires solving multiple linear matrix inequality optimisation problems to minimise an upper bound on a robust performance objective. An augmented polytopic uncertainty description is invoked to handle the input delays. The conservativeness of distributed MPC algorithm is reduced by utilising a sequence of feedback control laws. An iterative on-line algorithm for robust distributed MPC is developed to coordinate the distributed MPC controllers. Convergence and robust stability of the proposed distributed MPC are investigated. A numerical example is carried out to demonstrate the effectiveness of the proposed algorithm.
机译:在这项研究中,提出了一种设计具有时滞的多目标不确定网络控制系统的鲁棒分布式模型预测控制(MPC)设计方法。为了降低计算复杂度并提高灵活性,整个系统被分解为多个较小尺寸的子系统。对于每个子系统,提出的鲁棒分布式MPC算法都需要解决多个线性矩阵不等式优化问题,以最小化鲁棒性能目标的上限。调用增强的多面体不确定性描述来处理输入延迟。通过使用一系列反馈控制律,可以降低分布式MPC算法的保守性。开发了一种用于鲁棒分布式MPC的迭代在线算法,以协调分布式MPC控制器。研究了所提出的分布式MPC的收敛性和鲁棒稳定性。数值例子验证了所提算法的有效性。

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