Event-Based Distributed Control of Constrained Multi-Agent Systems

多智能体系统是一组相互作用以实现局部和全局目标的智能体。代理具有动态性，是空间分布的，可以通信，并且通常在动态、约束和目标方面是耦合的。典型的例子包括电力系统，其中代理是发电机、负载和存储，它们通过电网物理耦合，并通过通信网络、运输系统、灌溉系统和制造系统进行信息耦合。这些系统具有很高的技术、经济、生态和社会相关性，因此在过去几年中在学术界和工业界都受到了相当大的关注。多智能体系统的控制是一个非常具有挑战性的问题。这些挑战主要来自于巨大的计算和通信复杂性。为了应对这种复杂性，近年来人们提出了分布式控制和基于事件的控制。这些方法已被证明是非常通用和有效的。然而，对这些方法的研究仍处于起步阶段。特别是整体的方法仍然缺失。这就是这个项目开始的地方。该项目的目标包括为具有物理约束和信息约束的多代理系统同时设计控制器、调度程序、事件生成器和通信拓扑的整体方法。物理约束来自于执行器和装置的限制。信息约束源于共享且不完善的计算和通信资源，包括介质访问约束、通信和计算延迟以及数据包丢失。在项目中，采用了两种方法：基于事件的分布式协同设计（EBDC, Liu）和基于事件的分布式模型预测控制（EBDMPC, Görges）。EBDC基于控制器、调度程序、事件生成器和通信拓扑的鲁棒协同设计，这些协同设计主要是离线执行的，而EBDMPC则依赖于主要在线执行的最佳协同设计。这两种方法在复杂性和性能方面是互补的。由于离线协同设计，EBDC具有较低的复杂性，但性能相对较低；而EBDMPC具有较高的复杂性，但性能相对较高。这些方法具有很强的交互性，允许项目伙伴之间的密切合作。具体来说，分布式控制器设计、基于最优性条件的事件生成、通信拓扑设计、稳定性、可行性和最优性分析、分布式即插即用控制和分布式优化等方法将尽可能协同发展。在整个项目中，这些方法将被评估用于电力系统的分布式控制，并作为一个开放、模块化和可扩展的基于matlab的工具箱来实现。

Multi-agent systems are sets of agents interacting for achieving local and global objectives. The agents have dynamics, are spatially distributed, can communicate, and are often coupled in terms of dynamics, constraints, and objectives. Typical examples include power systems, where the agents are generators, loads, and storages which are physically coupled by the power grid and informationally coupled by a communication network, transportation systems, irrigation systems, and manufacturing systems. Such systems have a high technological, economical, ecological, and social relevance and have therefore received considerable attention both in academia and industry during the last years. The control of multi-agent systems is very challenging. The challenges primarily result from an enormous computation and communication complexity. To cope with this complexity, distributed control and event-based control have been proposed in very recent years. These methods have proved very versatile and effective. Research on these methods is, however, still in the beginning. Particularly holistic methods are still missing. This is where this project starts. The objective of the project consists in holistic methods for a simultaneous design of controllers, schedulers, event generators, and communication topologies for multi-agent systems with physical constraints and informational constraints. Physical constraints result from limitations in actuators and plants. Informational constraints stem from shared and imperfect computation and communication resources comprising medium access constraints, communication and computation delays, and packet losses. Within the project two approaches are pursued: event-based distributed codesign (EBDC, Liu) and event-based distributed model predictive control (EBDMPC, Görges). EBDC is based on a robust codesign of the controllers, scheduler, event generators, and communication topology which is performed largely offline while EBDMPC relies on an optimal codesign which is conducted mostly online. The approaches are complementary in terms of complexity and performance. EBDC has a low complexity but also a comparably lower performance due to the offline codesign while EBDMPC has a high complexity but also a comparably higher performance. The approaches have strong interactions, allowing a close cooperation between the project partners. Specifically methods for distributed controller design, event generation based on optimality conditions, communication topology design, stability, feasibility, and optimality analysis, distributed plug and play control and distributed optimization will be developed synergistically wherever possible. Throughout the project the methods will be evaluated for distributed control of power systems and implemented as an open, modular, and scalable MATLAB-based toolbox.