三维最优持久编队拓扑生成策略

针对智能体间的通信拓扑优化问题, 结合图论知识研究了三维空间中最优持久图的生成算法. 首先,利用刚度矩阵生成最优刚性图;然后,根据顶点连通度数的不同分别采取有向化操作方法, 通过逐层缩小最优刚性图范围的方式把刚性图持久化,生成了最优持久图;最后, 对三维空间中随机分布的智能体进行仿真实验,其结果验证了该算法的可行性和有效性, 此算法能降低编队拓扑的通信复杂度,减少通信能量消耗.     

多智能体系统最优持久编队自动生成

在最优刚性编队基础上,本文研究了多智能体系统的最优持久编队自动生成算法,所得算法能最大限度地减少维持编队结构稳定所需的信息交互量.首先,对于任意的最小刚性图.提出了缩减其范围的两种刚性逆操作;然后,设计了将包含于此两种操作中的无向边增加方向的规则,以使对应顶点的出度不大于2;并且在此基础上得到了任意最小持久图的生成算法,保证了最优持久编队的生成.最后,进行仿真研究,验证了提出算法的有效性.     

多智能体系统的最优持久编队生成策略

针对二维空间中减少智能体间通信链路的能量消耗问题,提出了一种基于最优刚性编队的最优持久编队生成算法.算法提出了针对智能体连通度数目的有向化操作方法,通过层层缩减最小刚性图范围的方式生成最优持久图,这种方法能对任意最小刚性图进行持久化,从理论上证明了算法的可操作性.仿真结果验证了算法的有效性.     

多无人机完全分布式有限时间编队控制

针对分布式通信网络,研究多无人机完全分布式编队生成和保持控制问题.基于滑模和自适应方法设计自适应耦合增益,进而结合与邻居无人机之间的相对状态设计一种新的有限时间编队控制器.该算法去掉了传统编队控制器依赖通信网络范围和拓扑及Leader无人机状态等全局信息的限制,基于Lyapunov理论证明无人机编队误差在有限时间可以收敛到边界可调的邻域内.对三维运动的多无人机编队进行仿真验证,结果显示,所设计的编队控制算法可以实现多无人机有限时间完全分布式编队生成和保持.     

无人机集群的微分平坦性与编队控制研究

本文研究了无人机集群的微分平坦性,给出了相对运动的微分平坦映射,并以此为基础设计了分布式编队控制器.运动规划方面,通过求解受约束的优化问题,实时生成期望编队轨迹和编队构型.运动控制方面,采用微分平坦映射将运动指令映射为每架无人机的期望状态和控制输入,而后利用局部误差反馈设计分布式编队控制器跟踪期望运动轨迹.针对群体运动的稳定性问题,本文运用李雅普诺夫稳定性理论证明了闭环系统的稳定性,给出了控制参数的选取条件.最后仿真验证了编队控制方法在未知环境下的运动控制效果.     

应用控制系统设计工具箱PIMCSD求解卫星编队重构问题

利用线性时变系统终端约束最优控制方法,为椭圆轨道卫星编队的队形重构控制问题设计了均衡耗能最优控制器.由于描述椭圆轨道卫星编队相对运动的Lawden方程是时变方程,给卫星编队重构的最优控制器设计带来一定的困难.利用基于精细积分算法的控制系统设计工具箱-PIMCSD进行系统设计,求解卫星编队重构所需的时变最优反馈控制律和前馈控制律,最后给出了由三颗卫星组成的编队队形重构控制仿真计算结果.     

多运动体分布式最优编队构型形成算法

针对分布式通信条件下的多运动体编队构型形成问题进行研究.考虑到个体的有限通信与感知能力,传统集中式求解算法无法适应实际需求,提出一种基于分布式交替映射凸优化的分布式时间最优编队构型形成算法,使得个体间仅依赖局部通信与局部计算实现编队构型的快速形成;将该问题建模为含有等式约束的分布式Minimax凸优化问题,提出基于虚拟等式约束函数的分布式交替映射凸优化算法实现求解;根据求解结果,各运动体采用RVO避障策略实现最优构型形成.针对含有100个运动体的最优编队构型形成问题进行仿真,验证了所提出算法的有效性.     

基于虚拟参考中心策略的无人机编队控制算法

基于虚拟参考中心策略解决了有向通信网络结构下的无人机编队协同控制问题,为具有权重不平衡有向通信网络的多无人机系统设计了合适的连续时间编队控制算法,使多无人机协作达到编队,并使得全局目标函数达到最小值。利用李雅普诺夫稳定性理论证明了该算法能使各无人机移动路径总和最短,协同实现全局最优编队。     

基于星载GPS卫星编队可视化仿真系统

针对研究星载GPS编队卫星自主导航算法及模型对编队的影响,为实际编队提高导航定位精度,结合数据库系统编制出了关于星载GPS编队卫星仿真系统。在分析卫星编队相对导航运动规律基础上,利用OPENGL及数据库技术对星载GPS空间圆编队,车轮式编队和水平圆编队进行了三维可视化仿真,给出了设计过程。考虑到编队卫星需要接收GPS信号进行自主导航,利用GPS星座可见性分析方法,实现星载GPS编队卫星的GPS星座选择。三维可视化仿真结合STK进行了验证。仿真系统已作为编队方案设计、编队飞行相对导航仿真算法设计的基础工具,还为将来各种航天器编队飞行应用技术及航天器对接技术提供可靠的试验基础数据和技术依据。     

基于混沌粒子群优化的低截获概率编队通信方法

为提高飞行器编队的低截获性能,提出一种新的低截获概率编队通信方法。将飞行器编队通信视为自适应优化问题,以飞行器节点的辐射功率和拓扑链路作为优化对象,利用混合混沌粒子群算法进行迭代计算,以实现飞行器编队的最优低截获通信。仿真结果表明,混沌粒子群方法在满足可靠通信的前提下,可有效降低编队辐射功率,提高通信拓扑不确定性,改善飞行器编队的低截获能力。     

Automatic generation of optimally rigid formations using decentralized methods

In this paper, decentralized methods of optimally rigid graphs generation for formation control are researched. The notion of optimally rigid graph is first defined in this paper to describe a special kind of rigid graphs. The optimally rigid graphs can be used to decrease the topology complexity of graphs while maintaining their shapes. To minimize the communication complexity of formations, we study the theory of optimally rigid formation generation. First, four important propositions are presented to demonstrate the feasibility of using a decentralized method to generate optimally rigid graphs. Then, a formation algorithm for multi-agent systems based on these propositions is proposed. At last, some simulation examples are given to show the efficiency of the proposed algorithm.     

一种多非完整移动机器人分布式编队控制方法

本文研究了多非完整移动机器人编队控制算法。在该算法中,参考轨迹被视为虚拟领导者,只有部分机器人可以接收到领导者信息,机器人之间只能进行局部信息交互。利用坐标变换将机器人系统的编队问题转化为变换后系统的一致性问题,在持续激励的条件下,设计了一种分布式控制算法,通过图论与Lyapunov 理论证明了该分布式控制算法可以使移动机器人队伍指数收敛于期望队形,并使队形的几何中心指数收敛到参考轨迹。最后,数值仿真验证了该控制算法的有效性。     

Hedonic coalition formation for optimal deployment

This paper presents a distributed algorithmic solution, termed Coalition formation and deployment algorithm , to achieve network configurations where agents cluster into coincident groups that are distributed optimally over the environment. The motivation for this problem comes from spatial estimation tasks executed with unreliable sensors. We propose a probabilistic strategy that combines a repeated game governing the formation of coalitions with a spatial motion component governing their location. For a class of probabilistic coalition switching laws, we establish the convergence of the agents to coincident groups of a desired size in finite time and the asymptotic convergence of the overall network to the optimal deployment, both with probability 1. We also investigate the algorithm’s time and communication complexity. Specifically, we upper bound the expected completion time of executions that use the proportional-to-number-of-unmatched-agents coalition switching law under arbitrary and complete communication topologies. We also upper bound the number of messages required per timestep to execute our strategy. The proposed algorithm is robust to agent addition and subtraction. From a coalitional game perspective, the algorithm is novel in that the players’ information is limited to the neighboring clusters. From a motion coordination perspective, the algorithm is novel because it brings together the basic tasks of rendezvous (individual agents into clusters) and deployment (clusters in the environment). Simulations illustrate the correctness, robustness, and complexity results.     

Collision-free formation generation and tracking of unmanned aerial vehicles based on physicomimetics approach

This paper investigates the problem of collision-free leader–follower formation generation and tracking of multiple fixed-wing unmanned aerial vehicles (UAVs). A group of UAVs, described by unicycle-type models subject to velocity constraints, are required to form a desired formation, while tracking a virtual leader and achieving collision-free flight. To handle this problem, a novel control law based on physicomimetics approach is proposed, which integrates the formation generation, formation tracking, and collision avoidance together. Physical forces are imitated to design artificial forces used in control laws that drive multiple UAVs to accomplish desired collaborative behaviors. Further, the virtual repulsion is embedded in the physicomimetics-based control scheme to achieve obstacle avoidance naturally. The artificial forces have similar meaning to the physical forces because of similar forms, which facilitates the design and adjustment of the control strategy. Specially, to deal with the speed constraints of fixed-wing UAVs, a saturation function is applied to modify the control laws and the stability is proved theoretically. Finally, numerical simulations and hardware-in-the-loop experiments are provided to verify the effectiveness of the proposed control scheme.     

基于队形向量的机器人部队队形控制

多智能体协作完成特定任务是多智能体领域的一个基本问题 .本文结合多智能体理论和基于队形向量的队形控制算法 ,提出了一种改进的基于队形向量的控制机器人部队形成任意形状的队形的分布式队形控制算法 DFC.仿真的实验结果证明 ,该算法比现有算法功能完备 ,控制简单     

Finite‐Time Optimal Formation Control for Second‐Order Multiagent Systems

This paper studies the problem of finite‐time optimal formation control for second‐order multiagent systems in situations where the formation time and/or the cost function need to be considered. The finite‐time optimal formation control laws are proposed for the cases with or without a leader, respectively. For the case of control being constrained, the time optimal formation problem is considered and an algorithm is designed to derive a feasible solution for the problem concerned. Although the feasible solution may not be optimal, it can provide a lower bound for time for the formation problem with control constraints. Once the given formation time is lower than this bound, the control constraints cannot be ensured. Finally, some numerical examples are given to illustrate the effectiveness of the theoretical results.     

Stability analysis of nonholonomic multiagent coordinate‐free formation control subject to communication delays

This paper investigates the convergence of nonholonomic multiagent coordinate‐free formation control to a prescribed target formation subject to communication delays by means of Lyapunov‐Krasovskii approach and smooth state‐feedback control laws. As a result, an iterative algorithm based on linear matrix inequalities is provided to obtain the worst‐case point‐to‐point delay under which the multiagent system is guaranteed to be stable. It is worth mentioning that: (i) the given algorithm holds for any connected communication topology and (ii) the formation control is coordinate‐free, that is, a common frame is not required to be shared between agents. The effectiveness of the given method is illustrated through simulation results.