基于零空间方法的四旋翼无人机避障与协同编队控制

针对四旋翼无人机在编队飞行执行任务时可能遭遇障碍物问题,考虑多无人机避障及机间避撞的需求,提出 1种基于零空间方法的四旋翼无人机避障与协同编队控制算法。首先,建立四旋翼无人机动力学模型,并建立虚拟控制量简化控制模型;其次,基于零空间方法进行避障与协同编队控制算法研究,将无人机任务执行分解为目标趋向任务、避障避撞任务和协同编队任务,并根据优先级进行任务融合得到期望速度;再次,基于 PID方法设计控制律;最后,通过仿真验证所提控制算法的有效性。所提方法可保证四旋翼无人机在编队飞行中遭遇障碍物时的飞行安全。     

基于多轨迹预测的飞机近地防撞技术研究

针对飞机近地飞行安全问题,提出了一种基于多轨迹预测的飞机近地防撞技术实现方法。建立了飞机近地防撞功能触发的架构逻辑和评价标准,设计了一套六自由度多轨迹实时预测的轨迹预估算法和防撞控制算法,将近地防撞模型与飞机模型结合起来,在数字仿真环境中验证整套算法的合理性。结果表明,基于多轨迹预测的飞机近地防撞算法实时性好,飞行轨迹预测准确性高,逻辑架构鲁棒性强,易于成果转化,具有很高的工程应用价值。     

Virtual target guidance-based distributed model predictive control for formation control of multiple UAVs

The paper proposes a Virtual Target Guidance (VTG)-based distributed Model Predictive Control (MPC) scheme for formation control of multiple Unmanned Aerial Vehicles (UAVs). First, a framework of distributed MPC scheme is designed in which each UAV only shares the information with its neighbors, and the obtained local Finite-Horizon Optimal Control Problem (FHOCP) can be solved by swarm intelligent optimization algorithm. Then, a VTG approach is developed and integrated into the distributed MPC scheme to achieve trajectory tracking and obstacle avoidance. Further, an event-triggered mechanism is proposed to reduce the computational burden for UAV formation control, which takes into consideration the predictive state errors as well as the convergence of cost function. Numerical simulations show that the proposed VTG-based distributed MPC scheme is more computationally efficient to achieve formation control of multiple UAVs in comparison with the traditional distributed MPC method.     

基于强化学习的多无人机避碰计算制导方法

针对大量固定翼无人机在有限空域内的协同避碰问题,提出了一种基于多智能体深度强化学习的计算制导方法.首先,将避碰制导过程抽象为序列决策问题,通过马尔可夫博弈理论对其进行数学描述.然后提出了一种基于深度神经网络技术的自主避碰制导决策方法,该网络使用改进的Actor-Critic模型进行训练,设计了实现该方法的机器学习架构,...     

基于罚函数序列凸规划的多无人机轨迹规划

多无人机（UAVs）轨迹规划是具有非线性运动约束和非凸路径约束的最优控制问题。引入序列凸规划思想,将非凸最优控制问题近似为一系列凸优化子问题,并利用成熟的凸优化算法进行求解,以更好地权衡最优性和时效性。首先,建立了多无人机协同轨迹规划的非凸最优控制模型。然后,利用离散化和凸近似方法将其转换为凸优化问题,包括对无人机运动模型的线性化,以及对威胁规避约束和无人机碰撞约束的凸化。同时,提出了一种离散点间的威胁规避方法,保证无人机在离散轨迹点间的飞行安全。在凸优化模型的基础上,给出了基于罚函数序列凸规划求解多无人机轨迹规划的具体框架。最后,通过数值仿真验证了方法的有效性,结果表明该方法在多机轨迹规划结果的最优性和时效性都要优于伪谱法,而且优势随编队数量的增加而增大。     

基于合作的冗余度双臂机器人的避碰研究

冗余度双臂机器人在危险或太空环境中具有极高的应用价值，但是实现有效的和实时的合作是很困难的。在合作的双臂机器人之间实现避碰是成功地应用冗余度双臂机器人的关健。尽管基于距离函数的方法已被证明简单和有效，但是不同的避碰点经常会产生不同的避磋结果，甚至会导致失败。本讨论了避碰点的选择问题，提出了一种新的避碰点选择方法，并用冗余度平面机器人对该方法进行了验证。     

基于群智机理的集群防碰撞控制

在执行作战任务以及民用中,无人机集群由于具备高可靠性和高效费比的特点而受到广泛关注;随着城市低空空域的开放,作战环境的动态复杂性剧增,对无人机集群防碰撞提出了严峻的挑战。针对无人机集群执行任务时的编队个体之间防碰撞以及遭遇突发障碍时的集群防碰撞问题,提出了基于群智机理的集群防碰撞控制方法。通过引入力学概念,设计了集群内部吸引力、排斥力以及编队构型力的模型;通过集群个体间的信息共享以及类脑知识发育,构建了基于群信息共享和类脑反射的无人机防碰撞模型。仿真结果表明：所提集群控制方法提高了集群的集结效率,而且在遭遇突发障碍时能够规避动态障碍,再次完成编队重构;群智机理的引入缩短了无人机集群面临突发障碍时的反应时间。     

星座碰撞规避的迭代学习构型保持方法CSCD

针对低轨卫星星座运行中地球引力摄动的周期特性,基于迭代学习控制(ILC)方法,提出了星座碰撞规避的迭代学习构型保持方法。该方法由反馈控制和ILC两部分构成,分别抑制卫星运行过程中的非周期摄动和周期摄动对构型保持精度的影响,进而在地球非球形引力摄动未知条件下,通过相对构型的精确保持实现对星座卫星碰撞的有效规避。仿真结果表明,在地球J摄动影响下,与传统反馈控制相比,ILC方法以更小的控制输入实现了轨道保持精度的显著提升,进而在星座卫星轨道高度相近的情形下显著降低了碰撞风险,且控制器可在保证收敛性能的前提下,实现启动时间的灵活选择。     

Event-triggered control for containment maneuvering of second-order MIMO multi-agent systems with unmatched uncertainties and disturbances

This paper is concerned with distributed containment maneuvering of second-order Multi-Input Multi-Output (MIMO) multi-agent systems with non-periodic communication and actuation. The agent is subject to unmatched nonlinear dynamics and external disturbances. Event-triggered containment maneuvering control methods is developed based on a modular design. Specifically, an estimator module is constructed based on neural networks and the non-periodic obtained follower information through event-triggered communication. Next, a controller module is designed by using the identified information from the estimator module and a third-order linear tracking differentiator. An event-triggered mechanism is introduced for updating the actuator. Then, a path update law is designed based on the non-periodic leader information through event-triggered communication. The closed-loop system cascaded by the estimation subsystem and control subsystem is proved to be input-to-state stable, and Zeno behavior is excluded in the control process. The proposed method is capable of reducing the consumption of communication and actuation. A simulation example is provided to substantiate the effectiveness of the proposed event-triggered control method for distributed containment maneuvering of second-order MIMO multi-agent systems.     

圆形轨迹导引下的无人机事件触发抗干扰环绕控制

针对内部不确定性以及外部环境摄动的目标环绕控制问题,在基于反步法的双层制导框架下,利用级联控制思想,提出了一种圆形轨迹导引下的四旋翼无人机事件触发抗扰环绕控制方法。在轨迹回路中,构建了可满足持续激励条件的目标位置估计器,保证仅通过视线方位角就能获取可满足最终一致有界条件的目标估计项。随后,基于目标的位置估计结果,设计了目标环绕控制律生成线速度指令,并通过方向向量场验证了该环绕制导律的有效性,消除了现有李雅普诺夫向量场制导(LVFG)对相对位置和目标速度的依赖。在姿态回路中,通过采用扩张状态观测器(ESO)补偿系统的集总不确定性,设计了基于相对阈值事件触发控制的姿态控制器,在有效降低控制器到执行机构之间信号传输频率的同时,实现了四旋翼无人机对静止/移动目标环绕。然后,借助输入状态稳定性定理证明了系统的稳定性。仿真结果表明,所提控制方案能够实现圆形轨迹导引下四旋翼无人机对静止/移动目标的环绕监视。     

基于改进A*算法的UUV冰下避障航迹规划算法

针对冰下避障航迹规划问题,提出了一种基于改进A*算法的三维冰下避障航迹规划算法.不同于传统的A*航迹规划算法,该算法结合了人工势场航迹规划算法的思想,将水下地形碰撞约束、海冰碰撞约束以及UUV巡航高度约束重新编排.算法分析表明,该避障航迹规划算法能够有效增强UUV冰下避障能力与定深巡航高度控制能力.基于改进的A*冰下避障航迹规划算法,给出了上述约束的设计方法并进行了仿真验证.仿真结果表明,基于上述约束的航迹规划算法具有良好的避障能力、巡航高度控制能力以及航行距离控制能力.     

无人机防相撞空中威胁态势的探测与告警研究

空中威胁态势探测与告警是无人机飞行防相撞预警的关键。为此,提出一种基于航迹预测的无人机防相撞空中威胁态势探测与告警方法。在该方法中,先采用滑动窗多项式拟合法对入侵机航迹进行动态预测,然后,在航迹预测基础上,利用无人机与入侵机飞行信息,建立针对入侵机的无人机动态避撞区,最后,结合静态保护区原理,对特定飞行场景下的无人机飞行冲突趋势、空中危险接近趋势和飞行碰撞趋势的探测与告警。仿真实例验证了所提出方法的有效性,也验证了其用于无人机飞行防相撞预警的可行性。     

固定翼无人机编队的启发分布式模型预测控制

针对无人机编队飞行控制中队形保持、路径规划、重构、防撞等多重功能需求,采用启发型分布式模型预测控制框架,将需求转化为多目标优化问题中的代价函数与相容性约束求解,实现了对无人机编队飞行的一体化控制.同时,采用分阶段式的轨迹规划算法,融合模型预测轨迹规划与多项式轨迹规划,利用多项式轨迹系数实现高效的邻居轨迹信息交互,从而增大了模型预测控制的预测范围,并降低了规划控制过程中的计算量与通信量.最后,通过9架无人机的协同避障编队仿真,证明了该方法的有效性.     

Target-enclosing affine formation control of two-layer networked spacecraft with collision avoidance

This paper addresses a target-enclosing problem for multiple spacecraft systems by proposing a two-layer affine formation control strategy. Compared with the existing methods, the adopted two-layer network structure in this paper is generally directed, which is suitable for practical space missions. Firstly, distributed finite-time sliding-mode estimators and formation controllers in both layers are designed separately to improve the flexibility of the formation control system. By introducing the properties of affine transformation into formation control protocol design, the controllers can be used to track different time-varying target formation patterns. Besides, multi-layer time-varying encirclements can be achieved with particular shapes to surround the moving target. In the sequel, by integrating adaptive neural networks and specialized artificial potential functions into backstepping controllers, the problems of uncertain Euler-Lagrange models, collision avoidance as well as formation reconfiguration are solved simultaneously. The stability of the proposed controllers is verified by the Lyapunov direct method. Finally, two simulation examples of triangle formation and more complex hexagon formation are presented to illustrate the feasibility of the theoretical results.     

基于预测控制的无人机编队内部避碰

针对无人机编队内部避碰问题,首先采用基于预测控制的方法,解决了在即将发生碰撞情况下无人机的航向调整问题;然后,建立了航路回归模型,解决了无人机避碰后,迅速回归预定航路的问题。仿真结果表明,文章给出的避碰方法能够有效解决无人机编队内部碰撞问题。     

交会对接任务碰撞规避策略制定研究简

针对交会对接任务目标飞行器与追踪器轨道运行特性,综合考虑规避策略计算方法与工程实际相结合的问题,提出高度规避、时间规避以及与正常轨控相结合的碰撞规避策略计算方法等三种空间目标碰撞规避策略计算方法.高度规避计算方法采用了Lambert飞行原理,用简化二体开普勒模型取代高精度轨道预报方法,迭代求解规避机动速度增量,实现了通过约束过交点与目标径向距离差得到速度增量的最优解;时间规避计算方法通过轨道周期与速度增量的关系,实现了通过约束过交点与目标的时间差得到速度增量的最优解;与正常轨控相结合的碰撞规避策略计算方法,在正常控制考虑冗余控制量的基础上,对控制策略的控制开始时间或沿迹方向的速度增量进行较小的修正,使两者通过碰撞点的时刻或径向距离错开,达到碰撞规避的目的,该方法不仅可以节省燃料、而且对任务的影响较小.通过对三种空间目标碰撞规避策略计算方法仿真分析结果表明,完全适用于交会对接任务,可为我国载人航天任务飞行安全提供技术保障.     

Robust formation control for missiles with obstacle avoidance

This paper investigates the robust formation control for missiles with obstacle avoidance.A sliding mode surface that is asymptotically stable is firstly presented by the collision avoidance potential function and hyperbolic tangent function. Based on the sliding mode surface, a robust formation controller with obstacle avoidance is designed for missiles. To improve the convergence rate,a finite-time controller which can deal with the formation control for missiles is given using an improved sli...     

Distributed event-triggered adaptive control for second-order nonlinear uncertain multi-agent systems

In this paper, the event-triggered consensus control problem for nonlinear uncertain multi-agent systems subject to unknown parameters and external disturbances is considered. The dynamics of subsystems are second-order with similar structures, and the nodes are connected by undirected graphs. The event-triggered mechanisms are not only utilized in the transmission of information from the controllers to the actuators, and from the sensors to the controllers within each agent, but also in the communication between agents. Based on the adaptive backstepping method, extra estimators are introduced to handle the unknown parameters, and the measurement errors that occur during the event-triggered communication are well handled by designing compensating terms for the control signals. The presented distributed event-triggered adaptive control laws can guarantee the boundness of the consensus tracking errors and the Zeno behavior is avoided. Meanwhile, the update frequency of the controllers and the load of communication burden are vastly reduced. The obtained control protocol is further applied to a multi-input multi-output second-order nonlinear multi-agent system, and the simulation results show the effectiveness and advantages of our proposed method.     

Inflight path planning replacing pure collision avoidance, usingADS-B

This paper proposes a method of collision avoidance planning using automatic dependent surveillance-broadcast (ADS-B) and dynamic programming (DP). It in essence allows air traffic control (ATC) within the cockpit for remote or uncontrolled airspace and is a step toward Free Flight. This paper reviews the approach to collision avoidance in the aircraft industry and to similar problems in other industries. DP is one solution method used in other industries for the problem of path planning to avoid collisions with fixed obstacles. The solution proposed here for the aircraft case uses DP applied to the moving obstacle case. The problem is first simplified by assuming fixed obstacles for the cost minimisation algorithms. These fixed obstacles are then moved with time and the minimisation process is started again. Although this method works well in most cases, situations can be constructed where this method fails, allowing a collision. A modified approach is proposed, where the movement of obstacles is included more explicitly in the cost minimisation algorithm. This modification allows solutions which are complete and ensures safe maneuvres and should be considered as an aid to the Traffic alert and Collision Avoidance System (TCAS)     

基于梯度下降法的翼伞系统最优分段航迹规划

传统最优控制航迹规划一般以逆风精确着陆、控制能量小为优化目标，但传统最优控制的操纵过程一般是一条连续变化的曲线，工程上不易实施；与之相比，传统分段航迹规划操纵简单，工程上容易实施，能实现逆风精确着陆的目标，但控制能耗大。为了兼顾逆风精确着陆、能耗低和控制操作简单等目标，提出了一种基于梯度下降法的翼伞最优分段航迹规划方法。该方法将控制变量参数化，将逆风精确着陆、控制能耗小、能实现避障等多目标优化问题转化为加权单目标优化问题，并通过梯度下降法求解得到分段常值最优归航航迹。所提算法与基于伪谱法的最优控制规划航迹和基于遗传算法的分段规划航迹进行了对比，算法仿真结果表明本文提出的最优分段航迹规划法既可以实现着陆精度高、控制能量小、逆风着陆和避障的优化目标，同时规划的航迹又由分段常值实现控制，工程上容易实施，兼顾了最优控制航迹规划和分段航迹规划的优点。