Event-Based Distributed Control of Constrained Multi-Agent Systems

多智能体系统是一组为实现局部和全局目标而相互作用的智能体。代理具有动态性，在空间上分布，可以通信，并且通常在动态，约束和目标方面耦合。典型的例子包括电力系统，其中代理是发电机，负载和存储器，它们通过电网物理耦合并通过通信网络信息耦合，运输系统，灌溉系统和制造系统。这种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非常具有挑战性的。这些挑战主要来自于巨大的计算和通信复杂性。为了科普这种复杂性，近年来提出了分布式控制和基于事件的控制。这些方法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。该项目的目标包括在整体的方法，同时设计的控制器，事件发生器，事件发生器和通信拓扑结构的多智能体系统的物理约束和信息约束。物理约束来自于执行器和设备的限制。信息约束源于共享和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分组丢失。在该项目中，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是基于一个强大的协同设计的控制器，调度器，事件发生器和通信拓扑结构，这是在很大程度上离线执行，而EBDMPC依赖于最佳的协同设计，这是主要在线进行。这些方法在复杂性和性能方面是互补的。EBDC具有较低的复杂度，但由于离线协同设计，性能也较低，而EBDMPC具有较高的复杂度，但性能也较高。这些方法具有很强的互动性，使项目合作伙伴之间能够密切合作。具体而言，分布式控制器设计，基于最优条件的事件生成，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的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，并作为一个开放的、模块化的、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.