复杂环境下时变信号的分布式平均跟踪问题研究

项目名称： 复杂环境下时变信号的分布式平均跟踪问题研究

项目编号： No.61473240

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 自动化技术、计算机技术

项目作者： 陈飞

作者单位： 东北大学

项目金额： 80万元

中文摘要： 近年来，具有分布式特性的多智能体系统引起了研究者的广泛关注，并逐步成为涉及多学科交叉的前沿热点领域。由于智能体外部环境的复杂性及研究问题自身的需求，智能体需要处理一些外部的、时变的信息。如何有效地利用这些信息，使之更好地服务于系统的全局控制目标，是一个亟待解决的问题。本项目以复杂环境下的分布式平均跟踪问题为研究内容，从网络的非对称性、状态的不可测性、初始值的鲁棒性、控制输入的不连续更新与饱和限制等角度入手，拟引入尺度变量解决非对称网络的分布式平均跟踪问题；拟构造基于观测器的算法，解决状态不可测的分布式平均跟踪问题；拟通过Laplace变换分析算法关于初始值的鲁棒性；拟结合采样控制与事件触发控制的思想，解决控制输入不连续更新的分布式平均跟踪问题；拟构造低增益的分布式平均跟踪算法，解决控制输入的饱和问题。本项目的研究结果将丰富分布式平均跟踪问题的研究内容，并为其实际应用提供理论基础与技术支持。

中文关键词： 非对称网络；输出反馈；采样控制；事件触发；输入饱和

英文摘要： In recent years, distributed multi-agent systems have received intensive attention, and have become a very hot multi-disiplinary research area. Due to the complexity of the external environment and the requirements of the research problems, agents need to handle external and time-varying information. It thus becomes an urgent issue to consider how to use the information effectively to better serve the global control objective of the system. This project studies the distributed average tracking problem in complex environments from the following perspectives: asymmetry of the network topology, state non-measurability, robustness to initialization conditions, discontinuous updates of the control inputs, and input saturation. Specifically, this project will introduce a scaling variable to solve the distributed average tracking problem under asymmetric network topologies; will construct observer-based algorithms to solve the distributed average tracking problem without state measurements; will use the Laplace transform to analyze the robustness of the system to the initialization conditions; will combine the ideas of sampled-data control and event-triggered control to solve the distributed average tracking problem with discontinuous control input updates; and will desgin low-gain feedback algorithms to solve the distributed average tracking problem with input saturations. The derived results will enrich the research topics on distributed average tracking, and provide theorectical foundation and technical support for its practical applications.

英文关键词： asymmetric network;output feedback;sampled-data control;event-triggered;input saturation