最小-最大联合模型预测控制算法

A. Maxim, J. Maestre, C. Caruntu, C. Lazar
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引用次数: 2

摘要

针对有界可加不确定性系统,提出了一种具有可行性保证的联合模型预测控制算法。该公式适用于通过输入耦合的子系统,它假设耦合变量为扰动,并以最小的信息交换确保鲁棒共识。仿真结果表明,联合方法具有与全集中式算法相似的性能,并且相对于分散和迭代最小-最大分布式模型预测控制器具有更高的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Min-Max Coalitional Model Predictive Control Algorithm
This paper proposes a coalitional model predictive control algorithm with feasibility guarantees for systems with bounded additive uncertainties. This formulation, suitable for sub-systems coupled through the inputs, assumes the coupling variables as disturbances and ensures a robust consensus with minimum information exchange. The simulation results show that the coalitional method has similar behaviour to the fully centralized algorithm and improved performance with respect to the decentralized and the iterative min-max distributed model predictive controllers.
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