基于多任务的无人机编队控制研究

考虑到多架无人机编队飞行的特点,将松散编队及协同思想应用到紧密编队控制中,提出了一个三架无人机协同作战编队的飞行控制系统设计方法;在编队飞行动力学模型的基础上,设计了基于特征结构配置的无人机横侧向控制律,进行指定航路的飞行控制;然后,设计编队控制器,两架僚机可紧紧跟随长机并保持队形稳定;仿真结果表明,设计的控制器可以控制多架无人机进行紧密编队飞行,具有一定的实用性和推广价值。     

基于非线性动态逆的无人机编队协同控制

针对多无人机在空间机动过程中的编队形成与保持控制问题,提出一种基于非线性动态逆的无人机编队控制方法.将编队控制过程分解为两步:首先给出分布式长机状态估计算法,各编队无人机根据"相邻"无人机状态解算自身的期望运动指令;其次是设计接于非线性动态逆的编队控制器,使各无人机快速跟踪其期望指令并形成和保持稳定队形.仿真实验表明,编队长机进行空间机动过程中,各僚机能够准确估计其状态,快速形成并维持队形稳定.     

基于神经网络的多机协同编队控制器设计

针对多架无人机协同编队飞行控制问题,设计了一种基于BP神经网络的无人机编队飞行控制器.以两机编队为单元,僚机同时跟踪长机和相邻僚机,根据相对位置和参考坐标系统,采用BP神经网络训练得到最佳的PID控制参数,设计三通道PID控制器并对编队系统进行分布式协同控制,使系统快速跟踪指令并保持编队队形.对四架无人机组成的编队系统进行仿真,系统编队可快速保持期望队形,表明设计的编队控制系统具有良好的稳定性和较强的抗干扰能力.     

伪卫星协同编队控制与仿真

为保持4颗编队伪卫星的最佳几何布局,设计了一种综合自适应神经网络编队控制器,利用李亚普诺夫稳定性理论证明了“长机-僚机”方式的两机编队系统的稳定性。以两机编队为单元,根据相对位置和参考坐标系统,采用综合自适应神经网络结构对伪卫星系统进行分布式协同编队控制,使系统快速跟踪指令并保持最佳编队队形。对以无人机为平台的4颗伪卫星编队进行仿真,结果表明僚机能够快速跟随长机飞行并保持最佳编队队形,证明该编队控制器具有良好的稳定性和鲁棒性。     

小型无人机编队飞行的控制律设计与仿真

针对一种小型无人机模型及其编队飞行的实际背景和限制条件,采用长一僚机（leader—wingman）编队模式,按前向、侧向和垂直方向3个通道分别设计了僚机编队控制律,从而使三维编队问题得以简化．对于多机编队的情况,应用基于长机模式（leadermode）和前机模式（frontmode）的2种编队控制策略,并通过仿真实验和比较分析,证实了长机模式的优越性．通过2架小型无人机编队队形保持和多架无人机在大机动飞行情况下的队形保持与队形变换等一系列仿真实验,验证了提出的编队飞行控制律的可行性和有效性．     

无人机编队飞行导航方法及其仿真研究

研究无人机导航优化编队问题,编队各成员的高精度定位是无人机协同编队飞行的关键技术和难点.为了提高编队定位的精度,提出了一种长机组合导航和长/僚机相对测量的编队成员导航定位方法,在编队导航系统模型的基础上,采用卡尔曼滤波原理估计出各成员的惯导误差,经校正后得到精确的导航信息,并进行仿真.仿真结果表明,改进的方法对所设计的长机与僚机的导航定位是完全可行的,编队各成员均获得较高的测地导航精度.     

基于三维程控的无人机协同编队飞行研究

基于三维程控飞行策略,对多无人机(UAV)协同编队飞行控制进行研究,提出一种多机同方位任务需求的编队控制方法.采用“长机-僚机”编队结构模式控制编队飞行,以编队中的长机航迹坐标为基准坐标系实现了僚机与长机相对位置一致的控制;实现了编队中所有无人机同时到达指定位置并保持速度相对稳定的控制.通过航路规划和编队遥调,实现了人工干预与自动控制结合的编队飞行策略.仿真结果表明,该方法具有较好的可实施性、管理性、应用性和安全性.     

基于领航-跟随的有人/无人机编队队形保持控制

针对有人/无人机编队飞行过程中的队形保持问题,采用领航-跟随策略设计一种有人/无人机编队队形保持控制器.首先从编队作战体系和控制原理角度设计有人/无人机编队控制系统结构;然后基于领航有人机与跟随无人机平面位姿的几何关系,建立编队内相对距离-角度运动学模型;最后在考虑僚机控制系统时变扰动的情况下,针对编队运动学模型特点设计动态反馈自适应编队队形保持控制器,并利用李雅普诺夫理论证明编队控制器的稳定性.仿真结果表明,所设计的控制器能够克服僚机控制模型不确定性带来的扰动影响,可以实现编队由初始误差到期望队形的快速调整以及稳定队形的保持.     

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.     

基于动态角色分配的一致性协同无人机编队控制

随着微电子技术、数字通信技术的飞速发展,无人机编队已应用到许多领域。针对无人机编队保持和编队中能耗问题,提出了一种基于动态角色分配的一致性协同无人机编队控制方法。根据无人机运动学模型设计了一种反馈线性化姿态控制器。在此基础上,基于长机僚机模式设计了一种一致性编队控制算法,提升了编队系统的鲁棒性。同时,设计了一种基于匈牙利算法动态角色分配方法,使多无人机在执行任务过程中可依据具体的周围环境情况来重新制定编队方案确定各无人机位置以此来缩小执行任务周期,同时减小整体能量消耗,并以5架无人机构成编队为例开展了编队飞行仿真分析。仿真结果表明,基于动态角色分配的一致性协同无人机编队控制算法保证了编队控制系统的控制精度和鲁棒性,有效地减小了整体的能量消耗。     

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.     

Cooperative Control of Multiple UAVs for Source Seeking

This paper considers the problem of unknown scalar field source seeking using multiple UAVs subject to input constraints. In this problem, each UAV can only measure the scalar field value at its current location. In order to seek the scalar field source, cooperation of multiple UAVs is carried out by adopting a leader-follower formation strategy. A least squares method is introduced to estimate the gradient of the scalar field at the leader UAV location based on the measurements of all UAVs. By using the estimated gradient, this paper proposes a guidance law for the heading of the leader UAV, and a sliding mode based heading rate controller is designed for the leader UAV to follow the desired heading angle. Furthermore, a heading rate controller is developed for each follower UAV to achieve circular formation around the leader UAV. Finally, simulation results are provided to demonstrate the effectiveness of the proposed approach.     

分布式多无人机编队控制系统仿真

研究一种能够控制多无人机编队的分布式控制方法,采用无人机的动态方程转化为跟随机和领航机间相对运动信号与希望的相对运动信号间的误差模型,然后设计了前馈控制器以使误差模型的平衡点位于坐标原点,最后采用反推法设计了反馈控制器以镇定坐标原点的平衡点。上述方法将领航机的信息视为外部系统产生的信号,为前馈控制器部分设计了内部模型以补偿这些外部信号的作用。同时还设计了能够估计所有误差信号的状态观测器以实现需要全部误差信息的反馈控制器。算例仿真表明了应用编队控制律,各无人机能够较快地形成希望的队列,并按希望队形稳定飞行,验证了前馈加反馈的编队控制方法的有效性。     

Cooperative Control of Multiple UAVs for Moving Source Seeking

Advances in multi-agent technologies and UAV technologies make it possible to take advantage of cooperation of multiple UAVs for source seeking. This paper focuses on moving source seeking using multiple UAVs with input constraints. Firstly, a least-squares method is introduced to estimate the gradient of the scalar field at the leader UAV location based on the measurements of all UAVs. Since the moving source velocity is unknown, an adaptive estimator is designed to obtain the velocity. Based on the estimated gradient and source velocity, a guidance law and a sliding mode based heading rate controller are proposed for the leader UAV to achieve level tracking. Heading rate controller for each follower UAV is also developed to achieve circular formation around the leader UAV. Furthermore, the gradient estimation error is analyzed and its influence on moving source velocity estimation and level tracking accuracy is explored as well. Finally, simulation results are provided to verify the proposed approach.     

基于领航位置信息的AUV三维编队控制方法

研究了自治水下机器人（Autonomous Underwater Vehicle,AUV）三维环境中编队控制问题,应用领航一跟随式队形控制方法,仅利用领航者的位置信息及期望编队队形得到虚拟机器人的航行轨迹及速度信息,作为跟随者的航行参考量,应用反步及滑模控制方法为跟随者设计自适应控制律,使其轨迹收敛于虚拟机器人的轨迹,从而与领航者保持期望位姿关系。随后,在具体AUV动力学模型上,利用MATLAB／SIMULINK平台进行了编队控制的仿真研究,实现了预期的控制效果,验证了算法的有效性及实用性。     

A collision-free formation reconfiguration control approach for Unmanned Aerial Vehicles

Formation flying of Unmanned Aerial Vehicles (UAVs) has gained a lot of interest due to its many potential advantages. Flying in formation allows wider sensing coverage area and in effect, this leads to improved surveillance and enhanced situational awareness. Also flying in formation eases coordination and data fusion. This paper presents the control architecture for fixed-wing UAV reconfiguration control using a novel combination of known techniques. The current premise is for the UAVs to assume their final target states within a specified time interval while avoiding collisions with one another or with an obstacle during the process. Some simulations are performed to assess the performance of the reconfiguration control scheme. The effects of the control parameters on the reconfiguration trajectories are also examined.     

Design and implementation of a leader-follower cooperative control system for unmanned helicopters

In this paper, we present a full scheme for the cooperative control of multiple unmanned aerial vehicle (UAV) helicopters. We adopt the leader-follower pattern to maintain a fixed geometrical formation while navigating the UAVs following certain trajectories. More specifically, the leader is commanded to fly on some predefined trajectories, and each follower is controlled to maintain its position in formation using the measurement of its inertial position and the information of the leader position and velocity, obtained through a wireless modem. More specifications are made for multiple UAV formation flight. In order to avoid possible collisions of UAV helicopters in the actual formation flight test, a collision avoidance scheme based on some predefined alert zones and protected zones is employed. Simulations and experimental results are presented to verify our design.     

多无人机航迹规划的自适应B样条算法

无人机集群能更高效地完成复杂和具有挑战性的任务,航迹规划和编队控制是无人机集群的研究重点。针对复杂环境下的无人机编队控制问题,提出了一种结合分段自适应B样条（Piecewise Adaptive B-Spline,PABS）方法的领航-跟随策略。采用滚动时域控制及快速粒子群优化算法为领航者无人机生成一条安全的参考航迹,并根据跟随者与领航者保持的几何关系为跟随者无人机生成参考航迹。针对生成的跟随者航迹不平滑以及可能与障碍物发生碰撞的问题,使用PABS方法对跟随者航迹进行平滑和避障处理。实验表明,使用滚动时域控制及快速粒子群优化算法及PABS方法能为领航-跟随策略下的无人机编队生成安全平滑的航迹,相比于圆弧插补技术,PABS方法能使航迹更光滑。     

固定翼无人机密集编队极速穿越策略研究

针对固定翼无人机密集编队穿越门框的任务场景,提出系统编队穿越方案.首先,根据机载相机测量信息,提出基于视线角的制导策略,能够快速调整机头指向对准门框;其次,为了提高成功穿越的可靠性以及解决视线遮挡问题,提出基于门框位置解算的协同制导策略;然后,针对复赛存在导航干扰情况,在水平方向上设计基于特征点测量的惯性导航算法,在垂直方向采用基于微分滤波的气压高度和升降率提取方法,并且利用视线角穿越门框,设计基于距离控制的编队控制律;最后,设计相应的固定翼无人机系统,并以7机编队的形式参加了2021年“无人争锋”极速穿越比赛,参赛结果验证了所提出极速穿越方法的有效性.     

Adaptive fractional-order nonsingular fast terminal sliding mode formation control of multiple quadrotor UAVs-based distributed estimator

This paper mainly solves two major problems that are unavoidable in leader–follower formation process of quadrotor UAV group: the existence of external uncertainty disturbance and communication limited between quadrotor unmanned aerial vehicle (UAV) group. To solve the problem that only one of the followers in the leader–follower formation can obtain the leader's information, an improved distributed estimator is proposed in this paper, which can accurately estimate the leader's information for each follower. In addition, in order to eliminate the influence of uncertain external disturbance on the performance of quadrotor UAV, an adaptive estimation law is designed based only on velocity and position variables. For the attitude and position subsystem of the quadrotor UAV, a sliding surface with fractional-order term is designed. Which makes the quadrotor UAV tracking error system obtain good robustness at the stage of reaching the sliding surface and fast convergence and accurate tracking performance in the sliding stage. Based on Lyapunov stability theory, the convergence results are analyzed strictly. The results show that the algorithm can make the position distance between leader and followers converge to the desired offset. Simulation results verify the effectiveness and superiority of the control algorithm.