论文标题
分布式经济模型预测控制 - 使用社会等级来解决非凸度
Distributed Economic Model Predictive Control -- Addressing Non-convexity Using Social Hierarchies
论文作者
论文摘要
本文介绍了一个新颖的概念，用于解决分布式经济模型预测控制（DEMPC）系统的成本功能中的非跨性别性。具体而言，所提出的算法使代理能够自组织成一个层次结构，该层次结构确定了做出控制决策的顺序。这个概念基于自然界中社会等级制度的形成。该算法的另一个功能是它不需要先验已知的固定设定点。相反，代理以真正分布和可扩展的方式协商这些目标。在提供算法的详细描述后，还提供了融合，递归可行性和有限的闭环稳定性的保证。最后，将提出的算法与使用学术数字示例相比，将所提出的算法与基本的平行分布式经济模型预测控制器进行了比较。
This paper introduces a novel concept for addressing non-convexity in the cost functions of distributed economic model predictive control (DEMPC) systems. Specifically, the proposed algorithm enables agents to self-organize into a hierarchy which determines the order in which control decisions are made. This concept is based on the formation of social hierarchies in nature. An additional feature of the algorithm is that it does not require stationary set-points that are known a priori. Rather, agents negotiate these targets in a truly distributed and scalable manner. Upon providing a detailed description of the algorithm, guarantees of convergence, recursive feasibility, and bounded closed-loop stability are also provided. Finally, the proposed algorithm is compared against a basic parallel distributed economic model predictive controller using an academic numerical example.
