Control and Optimization for Event-triggered Networked Autonomous Multi-agent Systems

事件触发的网络化自治多智能体系统的控制和优化

• 批准号: 391970891
• 负责人: Professor Dr.-Ing. Martin Buss
• 金额: --
• 依托单位: National Natural Science Foundation of China
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/391970891?language=en
• 关键词: Control; Optimization; Event; triggered; Networked

The well-known phrase - a champion team will defeat a team of champions - gives insight as to why research on cooperative control of multi-agent systems is seen as one of the most promising and exciting directions in current and future engineering technology. Teams of robotic agents cooperate and interact with each other to complete tasks such as search and rescue, surveillance coverage over a large area or environmental monitoring. Key to this is development of distributed control algorithms for each agent that collectively achieves the global objective.This project will advance existing results in distributed control algorithms and make new contributions by studying the energy cost of implementing the algorithms. Firstly, the framework of event-based control will be used to reduce energy consumption by sensing and actuating only when required, as opposed to most existing algorithms, which actuate and sense continuously. Furthermore, unlike existing results, we will study agents with complex robot dynamics. Secondly, the project will consider the energy consumed in achieving the cooperative task. Optimal controllers for different coordination tasks, such as formation control, will be designed to reduce energy consumption; currently only consensus tasks have been considered. Going beyond this, sophisticated measures of energy costs related agent technologies will be incorporated.The complementarity in skills of the groups led by PI Yu and PI Hirche means the groups are perfectly suited for collaboration on this project. PI Yu and the HDU team have particular strengths in formation control and distributed coordination and PI Hirche and the TUM team are known for their theoretical contributions to optimal control, event-based control and robotics. Given past successful collaborations, and the complementary of world-leading skills, we believe this project will also be successful in producing great research contributions.

众所周知的短语“冠军团队将击败冠军团队”深刻地解释了为什么多智能体系统的协作控制研究被视为当前和未来工程技术中最有前途和最令人兴奋的方向之一。机器人代理团队相互合作、互动，完成搜索救援、大面积监视覆盖或环境监测等任务。其关键是为每个智能体开发分布式控制算法，共同实现全局目标。该项目将推进分布式控制算法的现有成果，并通过研究实现算法的能源成本做出新的贡献。首先，基于事件的控制框架将用于通过仅在需要时进行感测和驱动来减少能耗，这与大多数现有算法连续地驱动和感测不同。 此外，与现有结果不同，我们将研究具有复杂机器人动力学的代理。其次，项目会考虑完成合作任务所消耗的能源。将设计针对不同协调任务（例如编队控制）的最优控制器，以降低能耗；目前仅考虑了共识任务。除此之外，还将纳入与能源成本相关的复杂代理技术。PI Yu 和 PI Hirche 领导的团队在技能上的互补性意味着这些团队非常适合在该项目上进行合作。 PI Yu和HDU团队在编队控制和分布式协调方面具有独特的优势，PI Hirche和TUM团队因其在最优控制、基于事件的控制和机器人技术方面的理论贡献而闻名。鉴于过去的成功合作以及世界领先技能的互补，我们相信该项目也将成功地做出巨大的研究贡献。