Centralized Multiport Networked Dynamic (CMND) systems have emerged as a key architecture with applications in several complex network systems, such as multilateral telerobotics and multi-agent control. These systems consist of a hub node/subsystem connecting with multiple remote nodes/subsystems via a networked architecture. One challenge for this system is stability, which can be affected by non-ideal network artifacts. Conventional passivity-based approaches can stabilize the system under specialized applications like small-scale networked systems. However, those conventional passive stabilizers have several restrictions, such as distributing compensation across subsystems in a decentralized manner, limiting flexibility, and, at the same time, relying on the restrictive assumptions of node passivity. This paper synthesizes a centralized optimal passivity-based stabilization framework for CMND systems. It consists of a centralized passivity observer monitoring overall energy flow and an optimal passivity controller that distributes the just-needed dissipation among various nodes, guaranteeing strict passivity and, thus, L2 stability. The proposed data-driven model-free approach, i.e., Tunable Centralized Optimal Passivity Control (TCoPC), optimizes total performance based on the prescribed dissipation distribution strategy while ensuring stability. The controller can put high dissipation loads on some sub-networks while relaxing the dissipation on other nodes. Simulation results demonstrate the proposed frameworks performance in a complex task under different time-varying delay scenarios while relaxing the remote nodes minimum phase and passivity assumption, enhancing the scalability and generalizability.

翻译：集中式多端口网络动态系统已成为多边遥操作和多智能体控制等复杂网络系统中的关键架构。该系统通过网络化架构将中心节点/子系统与多个远端节点/子系统相连接。此类系统面临的挑战之一在于稳定性可能受非理想网络效应影响。传统的基于无源性的方法可在小规模网络系统等特定应用场景中实现系统稳定，但这类传统无源稳定器存在诸多限制：需以分散方式在各子系统间分配补偿从而制约了灵活性，同时依赖于节点无源性的严格假设。本文为集中式多端口网络动态系统构建了一种基于集中式最优无源性的稳定框架。该框架包含监测整体能量流的集中式无源性观测器，以及在各节点间分配精确所需耗散的最优无源性控制器，从而保证严格无源性及L2稳定性。所提出的数据驱动无模型方法——可调集中最优无源性控制——在确保稳定性的前提下，基于预设耗散分配策略优化整体性能。该控制器可在部分子网络施加高耗散负载，同时降低其他节点的耗散需求。仿真结果表明，所提框架在不同时变延迟场景的复杂任务中具有优越性能，同时放宽了对远端节点最小相位和无源性的假设，增强了系统的可扩展性与泛化能力。