摘要复杂系统是目前很热门的研究课题，而蜂拥控制是复杂系统的核心问题之一。所以本 文主要探讨了蜂拥控制的相关知识。蜂拥控制的最大特点就是通过单个个体简单的运行 规则实现整个群体的一致性。正因为这样的特点，很多学者对此产生浓厚的兴趣。目前 蜂拥算法很多运用在多智能体系统中。例如对机器人的控制、飞行器编队的控制等。首 先，本文介绍了蜂拥控制发展的背景及历史，然后介绍了蜂拥控制的经典模型及算法。 具体研究了带有虚拟领导者的多智能体蜂拥算法，并证明了系统的稳定性。在此基础上， 加入了网络通信。研究了保证网络通信连续性情况下的蜂拥控制算法，并对此进行了 Matlab 仿真。最后观察仿真结果并得出结论：只要初始网络连通，此算法不仅可以保证 网络通信的连续性，还能使群体中所有智能体准确跟踪到虚拟领导者的位置和速度。77277

毕业论文关键词 复杂系统 蜂拥控制 多智能体 网络通信

毕业设计说明书外文摘要 

Title Design and simulation of complex system flocking algorithm in network communication environment

Abstract Complex system is a very hot research topic at present,and flocking control is one of the key problems in complex system。So this paper mainly discusses the related knowledge of flocking control。The biggest characteristic of flocking control is to realize the consistency of the whole group by the simple run rules of each inpidual。Because of this characteristic ,mamy scholars have a strong interest in it。Currently,the flocking algorithm is applied to multi agent system many times。For example,the control of the robot and the control of aircraft formation,etc。First of all,this paper introduces the background and history of the development of flocking control,then the classical model and algorithm of flocking control are introduced。The flocking algorithm with virtual leader is studied in detail,and the stability of the system is proved。On this basis,the network communication is added。The flocking control algorithm to guarantee the continuity of network communication is studied ,and the Matlab simulation is carried out。Finally,the simulation results are observed and the conclusion is drawn:as long as the intial network is connected,this algorithm can not only guarantee the continuity of the network communication,but also make all the agents in the group to track the location and speed of the virtual leader。

Keywords Complex system  Flocking control Multi-agent Network communication

本科毕业设计说明书 第 I  页

目 次

1 绪 论 …

1。1 引 言 1

1。2 国内外研究现状 3

1。3 文章的主要工作 4

2 预备知识 6

2。1 引言6

2。2Reynolds 模型 6

2。3Olfati 算法 8

2。4 小结10

3  改进蜂拥算法及其稳定性证明 11

3。1