发表机构
School of Electrical Engineering, Korea Advanced Institute of Science & Technology (KAIST)（韩国科学技术院电气工程学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种基于系统级综合的凸优化框架，实现通信架构与分布式控制器的协同设计，并通过近端ADMM分解保持可扩展性，数值实验验证了其有效性。
AI 中文摘要
随着网络化动力系统规模的扩大，分布式控制器架构设计已成为一个关键问题。为解决这一问题，先前的研究已将设计正则化（RFD）框架引入系统级综合（SLS），主要关注执行器和传感器的布置。然而，通信架构同样从根本上影响分布式控制的性能，而在SLS框架内对底层通信拓扑进行可扩展的显式协同设计仍然具有挑战性。本文提出了一种在SLS范式内对通信架构和分布式控制器进行协同设计的可扩展凸优化框架。我们显式刻画了由通信拓扑诱导的系统响应可行子空间，该子空间由通信邻接矩阵参数化，并与物理被控对象拓扑相分离。通过从该刻画子空间推导出通信链路范数，我们构建了一个用于通信架构协同设计的凸SLS问题。采用近端交替方向乘子法（ADMM）对优化问题进行适当分解，以保持其对大规模网络的可扩展性。数值实验验证了所提框架在优化闭环性能与通信架构复杂度之间权衡方面的有效性，同时也证实了其可扩展性。
英文摘要
As networked dynamical systems grow in scale, distributed controller architecture design has become a critical issue. To address this, prior studies have incorporated the regularization for design (RFD) framework into system-level synthesis (SLS), focusing primarily on actuator and sensor placement. However, communication architectures also fundamentally impact the performance of distributed control, and scalable explicit co-design of the underlying communication topology within SLS remains challenging. This paper proposes a scalable convex framework for the co-design of communication architectures and distributed controllers within the SLS paradigm. We explicitly characterize a communication topology-induced feasible subspace of system responses, parameterized by the communication adjacency matrix and separate from the physical plant topology. By deriving a communication link norm from this characterized subspace, we formulate a convex SLS problem for communication architecture co-design. A proximal ADMM scheme is employed to appropriately decompose the optimization problem in a manner that preserves scalability to large networks. Numerical experiments validate the efficacy of the proposed framework in optimizing the trade-off between closed-loop performance and communication architecture complexity, while also confirming its scalability.
Commentsto appear at 2026 IEEE Conference on Decision and Control (CDC)
