基于MAS的合作—竞争编队研究

基于牧羊犬跟羊群的自然现象,研究了一类具有合作—竞争拓扑的一阶多智能体系统的新型编队问题。针对每个智能体以领导—跟随者法设计了一种分布式编队控制算法,实现了合作—竞争交互网络的编队运动。利用结构平衡的独立强连通分量(SBiSCCs)推导出了一个充分条件,以确保所有智能体以分布方式进行合作—竞争编队运动。最后,通过数值仿真验证了理论结果,结果表明该算法可以保证一群智能体达到期望队形,实现合作—竞争编队运动。     

基于免疫多智能体的舰艇编队协同防空体系模型

借鉴生物免疫系统的性质和机制,结合多智能体理论与方法,提出了一种新的免疫多智能体网络(Immune Multi-Agent Network,IMAN)模型。根据舰艇编队协同防空体系和生物免疫系统在防御功能、自适应和自组织特性上相似的特点,将舰艇编队协同防空体系映射到生物免疫系统之中,设计了舰艇编队协同防空免疫智能体功能结构模型,并综合上述免疫多智能体网络模型IMAN及其免疫防御原理,构建了一种新颖的舰艇编队协同防空体系免疫多智能体网络模型,分析了舰艇编队协同防空体系免疫多智能体的免疫防御机制及其性质,旨在为舰艇编队协同防空体系研究开拓一种新思路,并为建立适合现代实战需要的作战仿真系统提供理论模型。     

舰艇编队协同防空体系免疫多智能体模型

针对舰艇编队协同防空问题, 根据舰艇编队协同防空体系与生物免疫系统防御机制和性质相似的特点, 实现了二者在结构和功能上的映射. 在此基础上, 结合多智能体理论与方法, 设计了舰艇编队协同防空体系的监测、调节和抗体等免疫智能体的功能结构模型, 构建出一种新颖的舰艇编队协同防空体系免疫多智能体(IMA)系统模型, 提出了免疫多智能体系统的形式化描述, 分析了舰艇编队协同防空体系免疫多智能体系统的免疫应答过程和机制. 该模型的防御机制具有自学习、自适应、自组织的特性, 充分体现了舰艇编队协同防空体系的协同防御机制和性质, 为舰艇编队协同防空体系研究开拓了一种新思路.     

基于动态拓扑有领航者的智能群体群集运动控制

对具有二次积分动态的智能群体跟随领航者实现群集运动编队,提出了一个分散控制方法对智能群体进行分散控制。基于动态时变有领航者的网络拓扑,用图论模型表示智能体之间的相互作用及通信关系,运用推广的Lyapunov理论、微分包含及非平滑分析进行了稳定性分析,并得到所有智能体速度方向收敛到同一方向并与领航者保持一致;所有智能体速度大小收敛并与领航者相同;互连的智能体之间没有碰撞发生;所有智能体的人工势场函数被最小化等重要结论。给出了一个仿真实例,验证了该方法的有效性。     

具有弱通讯的多智能体分布式自适应协同跟踪控制

针对具有弱通讯的高阶严反馈非线性多智能体系统,提出一种新颖的分布式自适应反演控制方法,并研究了该系统的协同跟踪控制问题。首先,以5个智能体作为被控对象,其中一个智能体以分布式结构组成“领航者-跟随者”编队模式,并且将领航者的运动速度作为整个编队系统的前行速度,其余智能体作为跟随者跟随领航者编队运动。其次,采用自适应反演方法,对系统中由于弱通讯导致的不确定参数进行自适应估计,并对系统设计补偿追踪控制律,使系统中的智能体能够实现自主跟踪时变的参考轨迹,最终以最优的轨迹避开障碍物,并保持期望队形运动。接着,根据Lyapunov稳定性理论,证明了所提方法的有效性。最后,通过仿真对比表明,所提方法能够使多智能体系统的横向、纵向跟踪误差以及参考轨迹的相对误差均实现快速收敛,并在跟踪过程中保持该系统渐近稳定。     

离散时间多智能体系统群集运动的快速收敛

针对具有干扰的多智能体系统的离散时间群集运动问题,提出了一种有限时间收敛的包容控制算法。运用现代控制理论、代数图论和线性矩阵不等式等分析工具对所提出的控制算法进行理论分析,得到了具有干扰的离散时间多智能体系统有限时间内实现群集运动的收敛条件。分析了动态多智能体实现包容控制的运动状态,同时讨论了该系统在理想情况下达到有限时间收敛的充分条件。最后,系统仿真验证了所得结论的正确性。     

有单一虚拟领导者的时延编队一致性

引入一种有单一虚拟领导者的存在通信时延的二阶多智能体编队控制模型,分析了时延对编队一致性的影响。通过构造Lyapunov-Krasovskii泛函,综合运用LMI方法,推导证明了有单一虚拟领导者的时延编队系统取得一致的条件。证明过程中引入自由权矩阵的思想,得到了系统取得一致性的时延的上界和相应的自由权矩阵。数值实例和仿真结果表明了方法的有效性。     

多移动机器人混合避障算法的编队策略

针对多移动机器人系统在未知静态障碍物环境下的编队避障问题,提出了一种多移动机器人混合避障算法的编队策略,使多移动机器人系统在整个运行过程中保证系统内不发生碰撞,并且在未知静态障碍物环境中能最大程度地保持队形进行有效避障,以及能够在较短时间到达指定目标点。该编队策略基于领航跟随法和人工势场法,将系统内机器人划分为领航机器人及跟随机器人,并根据各自角色任务的差异,对其采用了不同改进方法的人工势场法进行避障,形成一种混合避障算法,其中针对领航机器人提出了LAPF(leader artificial potential field)避障算法,该算法改进了传统人工势场法的斥力函数,解决了传统人工势场法极易陷入局部极值困境的问题,并有效缩短了避障过程所用时间。为保证整个系统运行过程及避障行为之后能够恢复队形保持系统稳定性,该编队策略利用一致性模型控制机器人的速度,使领航机器人与跟随机器人的状态趋于一致,进而保持队形。仿真结果验证了LAPF算法及该多移动机器人混合避障算法编队策略的有效性。     

多智能体系统的分布式预测控制器设计

针对多智能体系统的跟踪及编队控制问题,研究其分布式预测控制器的设计方法。考虑时变通讯拓扑情况,在优化问题中附加一项辅助约束,保证了优化问题的递归可行性及多智能体系统的闭环指数稳定性。在每个采样时刻,各智能体根据通讯拓扑实时更新其代价函数及辅助约束,通过求解带有状态、输入及辅助约束的优化问题来计算其控制输入。仿真结果验证了结论的有效性。     

有人/无人机编队队形集结控制研究

针对有人/无人机(manned/unmanned aerial vehicle, MAV/UAV)编队队形集结控制问题，设计了一种基于航迹规划-跟踪的MAV/UAV编队集结控制策略。首先，考虑编队队形集结边界约束与防碰撞约束条件，设计了一种基于Dubins曲线与协同模拟退火粒子群优化相结合的编队集结航迹规划算法。然后，以规划得到的集结航迹作为期望航迹，设计了一种双回路结构的非线性路径跟踪控制方法。最后，利用Matlab软件对设计的航迹规划与跟踪控制方法进行了仿真对比实验，仿真结果验证了方法的有效性和优越性。     

FLOCKING OF MULTI-AGENT DYNAMIC SYSTEMS WITH GUARANTEED GROUP CONNECTIVITY*

This paper investigates distributed flocking problem where the information exchange among agents is modeled by the communication topology changing with time. Previous research on this problem establishes group stabilization by assuming that the dynamic topology is connected all the time, which however cannot be guaranteed by most proposed distributed control laws. In this paper, a distributed algorithm to distill a necessary subgraph of the initial communication topology is presented. This subgraph covers all the vertices of the communication topology and is proved to be connected as long as the initial communication topology is connected. A distributed control law is then designed to pursue the flocking motion while preserving all the edges in this subgraph. In this way, connectivity can be preserved all the time, and flocking problem is thus solved only provided the initial communication topology of multi-agent system is connected.     

Time-Variant Consensus Tracking Control for Networked Planar Multi-Agent Systems with Non-Holonomic Constraints

A time-variant consensus tracking control problem for networked planar multi-agent systems with non-holonomic constraints is investigated in this paper. In the time-variant consensus tracking problem, a leader agent is expected to track a desired reference input, simultaneously, follower agents are expected to maintain a time-variant formation. To solve the time-variant consensus tracking problem of planar multi-agent systems with non-holonomic constraints, a time-variant consensus tracking control strategy is designed on the basis of an unidirectional topology structure. One of main contributions of this paper is the time-variant consensus tracking protocol for general time-variant formations of planar multi-agent systems with non-holonomic constraints, the other main contribution of this paper is an active predictive control strategy, where predictions of agents are generated actively, so that the computational efficiency is improved than passive approaches. The proposed control strategy is verified by two types of time-varying formations of wheeled mobile robots, and the experimental results show that the proposed control strategy is effective for general time-variant consensus tracking problems of planar multi-agent systems with non-holonomic constraints in local and worldwide networked environments.     

Flocking with General Local Interaction and Large Population

This paper studies a flocking model in which the interaction between agents is described by a general local nonlinear function depending on the distance between agents. The existing analysis provided sufficient conditions for flocking under an assumption imposed on the system's closed-loop states; however this assumption is hard to verify. To avoid this kind of assumption the authors introduce some new methods including large deviations theory and estimation of spectral radius of random geometric graphs. For uniformly and independently distributed initial states, the authors establish sufficient conditions and necessary conditions for flocking with large population. The results reveal that under some conditions, the critical interaction radius for flocking is almost the same as the critical radius for connectivity of the initial neighbor graph.     

移动机器人的快速终端滑模轨迹跟踪控制

针对基于动力学模型描述的非完整移动机器人轨迹跟踪问题,给出了一种快速终端滑模控制器设计方法,该方法结合反演(backstepping)设计和快速终端滑模控制的思想,实现了非完整移动机器人全局快速轨迹跟踪控制,并且能够在有限时间内完全跟踪上期望轨迹。该方法将系统分解为低阶子系统来处理,利用中间虚拟控制量简化了控制器的设计,具有直观的稳定性分析,设计方法简单。仿真结果验证了该控制器的正确性和有效性。     

The Exponential Stabilization of Uncertain Chained Form Systems of Mobile Robots Based on Visual Servoing

A system for a type of nonholonomic wheeled mobile robots equipped with an uncalibrated camera fixed to the ceiling is investigated. Based on the visual feedback and the state-input transformation, models of uncertain chained form systems are presented for the robot-camera systems. Then, new smooth time-varying feedback controllers are proposed to exponentially stabilize the uncertain chained system by using state-scaling and control theories for two cases. The exponential stabilities of the closed-loop uncertain systems are rigorously proved. Simulation results demonstrate the effectiveness of the proposed strategies.     

Robust Finite-Time Trajectory Tracking Control of Wheeled Mobile Robots with Parametric Uncertainties and Disturbances

In this paper, a robust finite-time tracking control scheme is proposed for wheeled mobile robots with parametric uncertainties and disturbances. To eliminate the effect of lumped uncertainties,a nonlinear extended state observer(NESO) is employed to estimate the unknown states as well as uncertainties, and the corresponding coefficients are tuned via pole placement technique. Based on the observation values, the finite-time sliding mode controller is presented to guarantee that both the sliding mode variables and tracking errors converge to zero within finite time. Simulation results are given to demonstrate the effectiveness of the proposed control method.     

Leader-following coordination of multi-agent systems with information feedback

Based on the strategy of information feedback from followers to the leader, flocking control of a group of agents with a leader is studied. The leader tracks a pre-defined trajectory and at the same time the leader uses the feedback information from followers to the leader to modify its motion. The advantage of this control scheme is that it reduces the tracking errors and improves the robustness of the team cohesion to followers’ faults. The results of simulation are provided to illustrate that information feedback can improve the performance of the system.     

多移动机器人圆形队列形成算法

该文提出一种多移动机器人圆形队列形成算法。在机器人数量不太大的条件下,通过迭代调节多机器人形成的多边形的边长和内角以实现在某一圆上均匀分布,再调节机器人与圆心的距离,最终使机器人均匀分布在一个指定半径的圆上。仿真结果验证了该算法的有效性。     

虚拟环境下农业移动机器人行为及其仿真建模

由于农业移动机器人的作业环境与对象的复杂性和不确定性,使机器人在作业时不能有效地获取导航知识以便对其行为进行决策。利用人工智能和虚拟现实技术,研究了移动机器人的复杂行为,构建虚拟环境和基于规则和案例的知识库,对机器人复杂行为分类,把复杂行为分解为简单、特定和已知的行为。对于不确定的和没有前驱知识的行为,利用相似案例和不确定推理为行为进行导航。然后,建立了多Agent行为决策系统,定义了该结构的六元函数,建立了消息和事件驱动机制,实现了虚拟环境下移动式机器人对水果的采摘行为及其仿真建模。