大型工厂协同分布式模型预测控制的最优性与稳定性

Mohamed. A. M. Osman, B. Kamaruddin, M. Ramasamy
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摘要

本文对线性系统的协同分布式模型预测控制方案进行了集中控制和分散控制的比较。该方案弥补了基于模型技术在地理分布控制器控制精度和计算效率上的不足。该控制策略的优点是能够收敛到集中最优解(帕累托最优),并产生能够保证闭环稳定的控制反馈。为简单起见,提出了两个子系统的过程,但该策略具有扩展到任意有限数量子系统的灵活性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimality and Stability of Cooperative Distributed Model Predictive Control in Large–scale Plant
This work presents a comparison between centralized and decentralized control for cooperative distributed model predictive control scheme for linear systems. The presented scheme compensates the lack of accuracy and computational efficiency of model based technique for the geographically distributed controllers.The advantages of this control strategy is the ability to converges to the centralized optimal solution (Pareto optimum) and generate a control feedback that able to insure the closed-loop stability. A process of two subsystems is presented for simplicity, however, the strategy has the flexibility to be extended for any finite number of subsystems.
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