基于最小-最大可行协同的分布式模型预测控制

Guoqi Zhong, Zhiyuan Liu, Hong Chen
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引用次数: 1

摘要

针对具有有界持续扰动、控制约束和耦合的线性系统,提出了基于最小-最大可行协作的分布式模型预测控制方法。由于存在干扰作为外部输入,稳定性分析基于输入到状态稳定性(ISS)理论而不是经典的Lyapunov理论。选择目标函数为ISpS-Lyapunov函数,得到输入-状态实际稳定性。算例说明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On min-max feasible cooperation-based distributed model predictive control
In this paper, the method of min-max feasible cooperation-based distributed model predictive control (FC-MPC) for linear system with bounded persistence disturbance, control constraints and coupling is presented. The stability analysis is based on the input-to-state stability (ISS) theory rather than the classical Lyapunov theory because of the existence of disturbance as the external input. The objective function is chosen as the ISpS-Lyapunov function and then the input-to-state practically stability is obtained. An example is given to illustrate the effectiveness of this method.
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