基于群集行为的分布式多无人机编队动态避障控制

针对无人机编队保持和动态障碍物规避控制问题,本文提出了一种新的基于群集行为的分布式多无人机编队控制和避障控制算法.首先考虑了由机间气流等因素带来的干扰,基于吸引/排斥势场和一致性方法,设计了分布式无人机编队的队形保持控制算法,对编队内无人机之间的距离进行控制.进一步考虑外部移动障碍对无人机编队的影响,引入了排斥势场产生...     

分布式多无人机的时变编队非线性控制设计

研究了基于分布式通信网络的多无人机时变编队控制问题,考虑到外界扰动对多无人机协同编队系统的影响,提出一种新的连续非线性鲁棒编队控制方法.首先基于一致性方法构造了分布式无人机编队误差系统,降低了编队控制器对全局编队信息的要求;然后采用一种基于误差符号函数积分的鲁棒控制算法补偿未知外界扰动的影响,提高了无人机编队系统的鲁棒性,并基于Lyapunov分析的方法,证明了多无人机编队误差的半全局渐进收敛性;最后在四旋翼无人机编队实验平台上进行了多无人机时变编队的实时实验验证,实验结果表明,所提出的分布式编队控制算法可以实现多无人机时变编队控制,且具有较好的协同性能和抗干扰能力.     

基于虚拟结构法的多移动机器人分布式预测控制

研究多移动机器人协同编队控制问题,提出一种基于虚拟结构的分布式预测控制算法.与现有编队控制方法相比,基于虚拟结构的方法可以使移动团队更加稳定地保持期望编队队形运动,通过将变换矩阵与虚拟结构相结合可以改善编队结构的灵活性,从而有效拓展该方法的应用范围.最后将所提出控制算法与现有编队控制方法进行对比仿真,结果验证了其有效性...     

多无人机系统分布式编队控制

利用具有虚拟领航者的二阶动态一致性协议讨论了三维空间内分布式无人机编队控制问题。利用反馈线性化的方法将无人机非线性动力学模型线性化,将控制输入转化为惯性坐标系中三个坐标轴方向的加速度。运用一致性算法求解线性化后的无人机模型,使无人机能够形成稳定的预期编队并跟随虚拟领航者沿特定航线以一定速度运动。定义了编队的误差函数并运用Lyapunov稳定性理论证明了系统的稳定性。仿真验证了模型和算法的有效性。     

基于方位信息的无人机编队控制设计与验证

本文主要研究了无人机编队的抗扰跟踪控制设计. 针对各无人机只能获取邻机方位信息的情况, 文章设计了一种新的非线性控制器以完成多无人机系统的编队形成与跟踪任务. 考虑到无人机系统易受外界扰动影响的特性, 采用Leader-Follower式编队方法, 通过引入Leader位置信息来矫正基于方位信息的无人机编队系统的位置漂移.将反步法设计结合自适应设计与鲁棒控制设计, 来补偿未知参数与未知外界扰动对多无人机编队系统造成的影响,提高了多无人机方位编队系统的鲁棒性. 然后, 基于Lyapunov分析方法证明了系统的稳定性. 最后, 搭建了四旋翼无人机编队实验平台, 进行了基于方位信息的编队形成与跟踪飞行实验, 并与PD控制器进行了对比实验. 飞行实验结果验证了算法的有效性与实用性.     

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.     

基于分布式模型预测控制的无人机编队控制

针对多四旋翼无人机编队在巡航飞行过程中队形形成和保持问题,采用分布式模型预测控制方法将该问题转化为在线滚动优化问题.建立线性时不变的编队运动模型,进而在考虑状态和输入约束,不考虑时延、外界干扰、噪声的情况下,利用领航跟随策略设计一种分布式模型预测控制器,通过引入自身和邻居的假设状态轨迹设计代价函数.其中邻居信息的交互是在有向、时不变通信拓扑结构下进行的.基于该控制器,无人机能够在跟踪目标轨迹的同时,快速形成预先设定的队形并保持队形飞行.通过引入终端等式约束保证系统稳定,进而将目标函数作为Lyapunov函数,给出编队系统渐近稳定的充分条件.最后,利用6架无人机仿真验证控制算法的有效性和优越性.     

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.     

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。     

Fixed-time backstepping distributed cooperative control for multiple unmanned aerial vehicles

This paper proposes a fixed-time backstepping distributed cooperative control scheme based on fixed-time extended state observer (FxTESO) for multiple unmanned aerial vehicles (UAVs). A fixed-time ESO, which is convergent independently of initial conditions, is designed to estimate and compensate the external disturbances in tracking process. Moreover, to eliminate the “explosion of complexity” in the traditional backstepping architecture, a nonlinear first-order filter is adopted to construct the distributed fixed-time control scheme. Based on the local information of neighboring UAVs, a fixed-time backstepping cooperative controller is designed. The proposed formation algorithm can be shown practicable for the UAV control system by using of Lyapunov stability theory and graph theory. Simulation results are given to demonstrate the effectiveness of the proposed control scheme.     

Distributed output-feedback formation tracking control for unmanned aerial vehicles

This paper considers the output-feedback formation problem of tracking a desired trajectory for a group of networked unmanned aerial vehicles (UAVs). By introducing a state observer, the controller for the non-holonomic UAV model can be designed without linear and angular velocities measurements. The formation robustness can be improved by applying the virtual structure and synchronising the path parameters. It is proved that, with the proposed control strategy, all the closed-loop signals are bounded and the formation tracking errors asymptotically converge to zero. Simulation results are given to illustrate the effectiveness of the proposed control strategy.     

有向切换通信拓扑下多无人机分布式编队控制

本文对多无人机分布式时变编队控制问题进行了研究. 无人机之间的通信拓扑假定是有向和切换的. 基于 自身状态与邻居状态的相对局部信息构建了分布式编队控制器. 通过引入一个恰当的编队误差向量, 将有向切换 通信拓扑下的多无人机编队问题转化为一个切换系统的镇定问题. 基于Lyapunov稳定性分析方法得到了达成编队 的充分性条件. 仿真实验结果验证了结论的有效性.     

无人艇全分布式动态事件触发编队控制

针对通信资源受限的多无人艇(USV)编队控制问题, 本文提出了一种动态事件触发数据传输机制以降低通信频率, 减少控制算法对系统带宽的占用. 首先, 基于滑模和自适应控制算法设计一种全分布式编队控制器, 使得所有编队成员在保持预设队形的同时能够完成对期望轨迹的跟踪. 与现有编队控制器相比, 该控制器不需要通信网络的全局信息. 然后, 基于Lyapunov稳定性理论证明了编队跟踪误差以及所有闭环信号都能达到稳定状态. 此外,该算法能够保证触发时间序列不表现出Zeno行为. 最后, 通过数值仿真验证了全分布式编队控制器的有效性     

多无人机模糊多目标分布式地面目标协同追踪

针对城市环境中多约束条件下多无人机协同追踪地面目标问题,综合考虑具有不同重要性等级的多个优化目标,提出了一种基于分布式预测控制的模糊多目标航迹规划方法.首先,考虑城市环境中建筑物对无人机视线遮挡、无人机和传感器能量消耗等因素,分别采用目标覆盖度、控制输入代价和开关量形式传感器能耗等为目标函数,将多无人机协同追踪航迹规划转化为多目标优化问题;然后,基于分布式预测控制框架,利用每架无人机未来有限时域内的预测状态,构建多无人机之间的避碰约束,并结合最小转弯半径等约束,形成分布式协同航迹规划模型;最后,针对多个优化目标的不同重要性等级要求,利用模糊满意优化思想将目标模糊化,并根据更重要目标具有更重要满意度的原则,将优先等级表示为松弛满意度序,通过在线求解得到有限时域内每架无人机的局部航迹;与传统多目标加权算法仿真结果对比,验证了所提方法的有效性,充分说明了该方法能够获得同时满足目标优化和重要性等级要求的最优航迹.     

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.     

Time-varying formation control for unmanned aerial vehicles with switching interaction topologies

Time-varying formation control problems for unmanned aerial vehicle (UAV) swarm systems with switching interaction topologies are studied. Necessary and sufficient conditions for UAV swarm systems with switching interaction topologies to achieve predefined time-varying formations are proposed. Based on the common Lyapunov functional approach and algebraic Riccati equation technique, an approach to design the formation protocol is presented. An explicit expression of the formation reference function is derived to describe the macroscopic movement of the whole UAV formation. A quadrotor formation platform consisting of four quadrotors is introduced. Outdoor experiments are performed to demonstrate the effectiveness of the theoretical results.     

Robust attitude control for tail‐sitter unmanned aerial vehicles in flight mode transitions

Tail‐sitter unmanned aerial vehicles (UAVs) can flight as rotorcrafts as well as fixed‐wing aircrafts, but it is hard to control the flight mode transition. The vehicle dynamics involves serious parametric uncertainties, highly nonlinear dynamics, and is easy to be affected by external disturbances, especially during the mode transition. This paper presents a robust control method for a kind of tail‐sitter UAVs to achieve the flight mode transition. The robust controller is proposed based on the state‐feedback control scheme and the robust compensation method. The proposed control method does not need to switch the coordinate system, the controller structure, or the controller parameters during the mode transitions. Theoretical analysis is given to guarantee the robustness stability of the designed flight control system. Numerical simulation results are presented to show the advantages of the proposed control method compared with the state‐feedback control method and the sliding mode control approach.