基于图和流体扰动算法的多无人车编队及避障研究

为解决多无人车编队在存在运动目标、移动威胁与突发威胁等多种情况的复杂环境中的避障问题,设计了一种基于刚性图论和流体扰动算法的多无人车编队避障控制算法。首先,针对编队控制问题,采用图论方法描述多无人车之间的协同关系,利用无人车之间的距离约束,基于反步控制理论设计领航-跟随编队控制器。李雅普诺夫分析表明,期望的编队形状是渐近稳定的。其次,针对复杂动态障碍物环境下的编队避障问题,设计了基于流体扰动算法的避障路径规划方法,由领航无人车规划出编队的行驶路径,实现编队的整体避障。最后,基于MATLAB的仿真结果验证了所提算法的有效性。     

基于模糊人工势场法的多智能体编队控制及避障方法

针对动态环境中多智能体编队控制及避障问题,提出了一种基于模糊人工势场法的编队方法。首先,在领航跟随法的框架下控制编队队形,在动态队形变换策略的异构模式下,使用人工势场法为多智能体编队中每个智能体规划避障路径;其次,利用模糊控制器控制跟随智能体追踪领航智能体,同时保持跟随智能体之间与领航智能体的相对距离,遇到未知障碍物时,及时保持多智能体编队之间的队形并避免碰撞障碍物。针对人工势场法在引力增量系数和斥力增量系数设置的局限性,利用模糊控制器选择出适应环境的增量系数。Matlab仿真实验结果表明,该方法能够有效地解决复杂环境下多智能体编队控制及避障问题,使用效率函数对实验数据进行分析,验证了所优化方法的合理性和有效性。     

复杂地形环境下多机器人编队控制方法

针对复杂地形地面崎岖起伏的特点,提出了一种多机器人系统编队控制方法.首先,分析了复杂地形环境下的系统队形模型.通过建立三维地形环境下编队系统的误差模型,并运用空间投影法将其映射到二维平面上,对系统的编队误差进行分析.然后利用李雅普诺夫函数构造控制器,并根据环境中的特定地形设计相应的编队行驶策略,实现了多机器人系统在复杂地形环境下的编队控制.最后,通过3种典型复杂地形环境下两种非完整移动机器人的编队仿真,验证了该方法的有效性.     

卫星编队长期保持与控制比较研究

卫星编队飞行的难点之一是在复杂干扰力环境下控制队形.近圆轨道,编队控制充分考虑了J_2摄动等各种干扰对相对轨道构形的影响.以空间二体运动的Hill方程为基础建立相对运动动力学方程.分别采用基于线性二次调节器、李亚普诺夫理论以及零控脱靶量的方法设计了编队控制器,对干扰力作用下卫星编队长期保持的不同控制方法进行了比较研究,并对三种编队控制方法的控制精度、能量消耗进行了仿真分析.研究表明,对于编队的长期三种保持控制方法都是有效的,但基于零控脱靶量的编队控制方法更简单、性能好、实用性强,是一种较为理想的编队控制方法.     

移动机器人的队形控制及其主动避障

在这篇论文中, 我们利用一个统一的算法框架来解决移动机器人的队形控制和主动避障问题, 使得编队中的从机器人在避开障碍物的同时, 能够与被跟踪的主机器人保持期望的相对距离或相对方位. 在现有的关于主—从跟踪编队控制的文献中, 为了实现对主机器人快速准确的跟踪, 从机器人在跟踪控制时需要主机器人在惯性坐标系下的绝对运动速度作为队形跟踪控制器的输入. 然而, 在一些环境中, 主机器人的绝对运动状态很难获得. 这里, 我们将利用主—从机器人之间的相对速度来建立机器人编队系统的运动学模型. 基于这个模型的编队控制方法将不再需要测量主机器人的绝对运动速度. 进一步地, 上述的建模和控制方法被扩展为一个移动机器人的动态避障方法, 该方法利用机器人与障碍物之间相对运动状态作为避障控制器的信息输入. 利用由三个非完整移动机器人组成的多机器人系统, 验证了所提出编队控制方法的有效性.     

无人机编队队形保持变换控制器设计

研究无人机编队队形保持变换的控制设计问题.由于控制系统队形跟踪应保证姿态的稳定性,针对两架无人机在“长机-僚机”编队结构中的左菱形编队飞行控制系统,为了有效控制飞行队形,保持变换,提出了根据编队飞行的几何关系推导编队相对运动学方程,结合无人机的自动驾驶仪模型建立了相应的编队飞行线性化数学模型.采用PID控制方法分别对速度、航向和高度设计了一种能通过控制编队间距实现队形变换的三维编队队形保持变换的控制器,并进行仿真.仿真结果表明所设计的控制器能够有效地控制无人机编队,在飞行过程中可以稳定地保持队形,并能根据任务要求合理进行编队,并无碰撞,为设计提供了依据.     

一种船队编队控制的backstepping 方法

针对多船舶之间的协同合作问题,对船舶的编队控制进行了研究.通过运用领航者-跟随者方法,选择在Cartesian坐标系下建立新的船队编队控制模型,基于这种模型,利用反步技术和李亚普诺夫理论设计了一种可使船队按期望队形航行的船队编队控制器.通过考虑领队船舶与跟随船舶的航向角误差,保证了跟随船舶航向角的稳定性,从而避免其在航行过程中不断振荡.最后对所设计的控制方法的正确性及有效性进行了仿真验证.     

一种基于应力矩阵的无人机集群队形变换控制方法

针对复杂环境下无人机集群队形变换与编队控制问题,提出一种可抑制外部干扰的无人机集群队形变换策略,设计基于滑模的编队控制方法.首先,考虑无人机集群中存在多个领导者,提出一种“双层领导者-跟随者”无人机集群协同队形变换控制策略,实现障碍环境下的编队队形变换;然后,基于图论、一致性理论和滑模控制理论设计针对无人机集群存在外部干扰条件下的从机时变编队控制律,能够实现无人机编队按几何参数和几何图案连续变化;其次,通过构造Lyapunov函数证明在扰动条件下多领导者无人机集群系统队形变换的稳定性;最后,利用数值仿真验证所提出队形变换控制方法的有效性.     

基于鸽群行为机制的多无人机自主编队

受启发于无人机(unmanned aerial vehicle,UAV)编队飞行与生物群体社会性行为的相似性,本文提出了一种基于鸽群行为机制的多无人机自主编队控制方法.首先通过模仿鸽群特有的层级行为,建立了鸽群行为机制模型.该模型在已有群集模型基础上,采用有向图和人工势场理论对鸽群中的拓扑结构和领导机制进行建模.在深入分析无人机自主编队飞行仿生机理的基础上,设计了一种基于鸽群行为机制的无人机自主编队控制器.该控制器以鸽群行为机制模型为核心,还包含两个辅助环节,即控制指令解算器和状态转换器.最后,通过系列仿真实验验证了无人机群可在本文所设计的无人机自主编队控制器作用下形成预期的编队队形,并可在复杂长机运动条件下保持队形.     

无人机三维编队飞行的鲁棒H∞控制器设计

针对无人机编队控制中模型不确定性与外干扰同时存在的情况,首先基于无人机自身的自动驾驶仪和编队运动学关系建立了无入机编队的三维数学模型,这种建模方式物理意义明晰;进而提出一种基于鲁棒H∞控制理论的编队控制器设计方法,按前向、侧向和垂直方向3个通道分别设计控制律,降低了鲁棒控制器的调参难度,简化了三维编队控制问题.仿真结果表明了所设计的控制器的有效性,可实现无碰撞、快速、稳定地保持和调整无人机编队队形,具有良好的鲁棒性能.     

智能小车联网组队方法的设计与实现

随着5G技术的到来,物联网技术的发展不可限量,而在智能交通领域中起着举足轻重的无人驾驶技术和车联网技术必定成为未来研究的热点。那么如何通过车联网技术控制无人驾驶智能车辆进行联网组队也就成为研究的焦点问题。为此,模拟实现了无人驾驶智能小车联网组队运行的全过程。首先介绍了系统总体的设计方案,接着在STM32嵌入式开发平台下进行智能小车的硬件设计,然后介绍了如何利用ZigBee无线通信技术实现无人驾驶智能小车与智能网关之间的通信协议和相应的软件实现方案,最后进行了相应的测试。结果表明,本次设计完成了智能小车在行驶过程中接收和执行控制命令以快速组队的功能。实现了多辆智能小车排列“一”字、“V”字、“X”形、矩形、菱形五种组队队形。     

Formation tracking of multi-vehicle systems in unknown environments using a multi-region control scheme

In this paper, a multi-region control scheme is proposed for a formation of nonholonomic vehicles to track a reference trajectory while avoiding collisions and preserving network connectivity in unknown environments. The proposed control scheme defines three regions, safe region, dangerous region and transition region. In different regions, priority is given to different control objectives. In safe region where trajectory tracking holds the priority, the proposed control scheme guarantees bounded tracking of the reference trajectory for each vehicle. In dangerous region where avoidance control is the main objective, a new bounded potential function is designed to characterise constraints of obstacle and inter-vehicle collision avoidance as well as connectivity maintenance. By introducing a series of transition functions, smooth switching between trajectory tracking and avoidance control is achieved in transition region. It has been proved that each vehicle can track its reference trajectory while satisfying the constraints simultaneously with a bounded controller which means that the proposed control scheme satisfies input constraints by properly tuning parameters. Simulation results demonstrate the effectiveness of the proposed method.     

A Scalable Adaptive Approach to Multi-Vehicle Formation Control with Obstacle Avoidance

This paper deals with the problem of distributed formation tracking control and obstacle avoidance of multi-vehicle systems (MVSs) in complex obstacle-laden environments. The MVS under consideration consists of a leader vehicle with an unknown control input and a group of follower vehicles, connected via a directed interaction topology, subject to simultaneous unknown heterogeneous nonlinearities and external disturbances. The central aim is to achieve effective and collision-free formation tracking control for the nonlinear and uncertain MVS with obstacles encountered in formation maneuvering, while not demanding global information of the interaction topology. Toward this goal, a radial basis function neural network is used to model the unknown nonlinearity of vehicle dynamics in each vehicle and repulsive potentials are employed for obstacle avoidance. Furthermore, a scalable distributed adaptive formation tracking control protocol with a built-in obstacle avoidance mechanism is developed. It is proved that, with the proposed protocol, the resulting formation tracking errors are uniformly ultimately bounded and obstacle collision avoidance is guaranteed. Comprehensive simulation results are elaborated to substantiate the effectiveness and the promising collision avoidance performance of the proposed scalable adaptive formation control approach.      

Decentralised Formation Control and Stability Analysis for Multi-vehicle Cooperative Manoeuvre

Multi-vehicle cooperative formation control problem is an important and typical topic of research on multi-agent system. This paper presents a formation stability conjecture to conceive a new methodology for solving the decentralised multivehicle formation control problem. It employs the "extensiondecomposition-aggregation" scheme to transform the complex multi-agent control problem into a group of sub-problems which is able to be solved conveniently. Based on this methodology, it is proved that if all the individual augmented subsystems can be stabilised by using any approach, the overall formation system is not only asymptotically but also exponentially stable in the sense of Lyapunov within a neighbourhood of the desired formation. Simulation study on 6-DOF aerial vehicles (Aerosonde UAVs) has been performed to verify the achieved formation stability result. The proposed multi-vehicle formation control strategy can be conveniently extended to other cooperative control problems of multi-agent systems.      

基于庞特里亚金极小值原理的多运载体有限时间编队控制

研究基于庞特里亚金极小值原理的多运载体有限时间编队问题.运载体刻画为欧氏群切丛上演化的全驱动刚体动力学模型.编队机动时间以及队形的几何结构是由编队任务指定的.对于期望的队形,首先利用庞特里亚金最小值原理给出了开环最优控制.为了克服开环控制对扰动的敏感性并增加针对初始条件不确定性摄动的鲁棒性,在假定运载体间通讯为全联通的模式下,通过反馈将系统当前状态作为初始状态,当前时刻作为初始时刻,进一步将开环控制律转化为闭环形式.为了验证所得结果,给出了平面及空间运载体编队的仿真算例.     

Distributed control of angle-constrained cyclic formations using bearing-only measurements

This paper studies distributed control of multi-vehicle formations with angle constraints using bearing-only measurements. It is assumed that each vehicle can only measure the local bearings of their neighbors and there are no wireless communications among the vehicles. The desired formation is a cyclic one, whose underlying information flow is described by an undirected cycle graph. We propose a distributed bearing-only formation control law that ensures local exponential or finite-time stability. Collision avoidance between any vehicles can be locally guaranteed in the absence of inter-vehicle distance measurements.     

Nonlinear Adaptive Close Formation Control of Unmanned Aerial Vehicles

This paper treats the question of formationflight control of multiple unmanned aerial vehicles (UAVs). Inclose formation the wing UAV motion is affected by the vortexof the adjacent lead aircraft. The forces produced by these vorticesare complex functions of the relative position coordinates ofthe UAVs. In this paper, these forces are treated as unknownfunctions. For simplicity, it is assumed that the UAVs have autopilotsfor heading-, altitude-, and Mach-hold in the inner loops. Anadaptive control law is derived for the position control of thewing aircraft based on a backstepping design technique. In theclosed-loop system, commanded separation trajectories are asymptoticallytracked by each wing aircraft while the lead UAV is maneuvering.It is seen that an overparametrization in the design is essentialfor the decentralization of the control system. These resultsare applied to formation flight control of two UAVs and simulationresults are obtained. These results show that the wing UAV followsprecisely the reference separation trajectories in spite of theuncertainties in the aerodynamic coefficients, while the leadaircraft maneuvers.     

基于虚拟结构法的分布式多无人机鲁棒编队控制

针对多无人机编队控制(UAVs)问题, 本文提出了一种基于虚拟结构法的非线性鲁棒控制算法. 首先将编队 控制问题转化成两个子问题: 在惯性坐标系下虚拟刚体(VRB)光滑轨迹的生成设计, 以及在虚拟刚体坐标系下的无 人机编队队形控制设计. 针对部分无人机无法直接获取虚拟刚体状态的约束, 通过引入相邻无人机的跟踪状态, 实 现了分布式的编队控制. 同时, 考虑多无人机近距离编队飞行时相互间的气流扰动影响, 设计了基于supertwisting 的鲁棒控制算法, 提高了编队系统的控制精度和稳定性. 利用Lyapunov稳定性分析方法, 证明了位置跟踪误差在 有限时间内收敛到滑模面, 得到闭环系统全局渐近稳定的结果. 最后通过实际飞行实验, 验证了所提控制算法的有 效性和鲁棒性.     

Robust time‐varying formation control for multiple underwater vehicles subject to nonlinearities and uncertainties

This paper addresses the robust formation control problem for multiple autonomous underwater vehicles (AUVs) to achieve the desired formation trajectory and time‐varying formation pattern and to align the vehicle attitudes. The dynamics of each AUV system involves parameter variations, nonlinear dynamics, and external disturbances. A robust distributed formation control protocol is developed based on the graph theory and the robust compensation theory. It is proven that the tracking errors of the global uncertain system can converge into a given neighborhood of the origin in a finite time. Simulation results substantiate the effectiveness of the developed formation control method for multiple AUVs subject to nonlinearities and uncertainties.     

Formation stability analysis of unmanned multi-vehicles under interconnection topologies

In this paper, the overall formation stability of an unmanned multi-vehicle is mathematically presented under interconnection topologies. A novel definition of formation error is first given and followed by the proposed formation stability hypothesis. Based on this hypothesis, a unique extension–decomposition–aggregation scheme is then employed to support the stability analysis for the overall multi-vehicle formation under a mesh topology. It is proved that the overall formation control system consisting of N number of nonlinear vehicles is not only asymptotically stable, but also exponentially stable in the sense of Lyapunov within a neighbourhood of the desired formation. This technique is shown to be applicable for a mesh topology but is equally applicable for other topologies. A simulation study of the formation manoeuvre of multiple Aerosonde UAVs (unmanned aerial vehicles), in 3-D space, is finally carried out verifying the achieved formation stability result.