We present a hierarchical control scheme for large-scale systems whose components can exchange information through a data network. The main goal of the supervisory layer is to find the best compromise between control performance and communicational costs by actively modifying the network topology. The actions taken at the supervisory layer alter the control agents' knowledge of the complete system, and the set of agents with which they can communicate. Each group of linked subsystems, or coalition, is independently controlled based on a decentralized model predictive control (MPC) scheme, managed at the bottom layer. Hard constraints on the inputs are imposed, while soft constraints on the states are considered to avoid feasibility issues. The performance of the proposed control scheme is validated on a model of the Dez irrigation canal, implemented on the accurate simulator for water systems SOBEK. Finally, the results are compared with those obtained using a centralized MPC controller.

翻译：本文提出一种适用于大规模系统的分层控制方案，该系统各组件可通过数据网络交换信息。监督层的主要目标是通过主动修改网络拓扑结构，在控制性能与通信成本之间寻求最佳折衷。监督层采取的行动会改变控制代理对完整系统的认知，并影响其可通信的代理集合。每个相互关联的子系统组（即联盟）均基于分散式模型预测控制方案进行独立控制，该方案由底层管理。方案对输入施加硬约束，同时考虑对状态的软约束以避免可行性问题。所提控制方案在Dez灌溉渠模型上进行了性能验证，该模型基于精确的水系统模拟器SOBEK实现。最后，将所得结果与采用集中式模型预测控制器获得的结果进行了对比。