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     

多无人水面艇协同海上溢油羽流监测

本文讨论多无人水面艇协同海上溢油污染羽流监测问题,其中羽流扩张过程是由二维空间对流–扩散方程描述.本文的主要目标是为水面无人艇构建基于领导–跟随–锚的协同控制算法,实现其对羽流边界的动态合围与实时跟踪,其中羽流边界是一个预先设定阈值的水平集合.为此,选择两艘无人水面艇分别将其设定为边界领导艇和边界锚艇,并将其余艇设定为...     

一种双无人机协同跟踪地面移动目标方法

针对通信延时情况下双无人机协同跟踪地面移动目标问题进行研究, 构建了基于分布式遗传算法和滚动时域优化结合的目标跟踪航迹规划算法模型。考虑到通信延时会增加目标状态信息数据融合时的误差, 导致无人机跟踪任务效果变差, 结合递推最小二乘滤波和加权最小二乘估计设计了融合方法, 来融合处理目标状态信息; 考虑到无人机对目标的观测效果与未来时刻的目标状态信息密切相关, 采用递推最小二乘滤波预测目标的状态信息, 结合分布式遗传算法和滚动时域优化设计了双无人机目标跟踪航迹规划算法。适应度函数考虑了无人机和目标之间的距离、无人机之间的通信距离、无人机之间的通信角度。仿真结果表明：该协同跟踪方法能够较好地完成跟踪任务; 与一架无人机跟踪相比误差明显减小, 并且可以减小通信延时带来的跟踪误差。     

无人机编队飞行的分布式控制策略与控制器设计

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,分析了编队飞行所必须涉及的队形保持、约束条件以及行为协调等关键性问题,进而引入分布式编队飞行控制策略并简要介绍了其优越性.根据分布式策略的层级概念,先后讨论了单机控制器的设计与上层的编队控制器的设计.最后分别进行了单机的FDC(flight dynamic and control)仿真和双机编队仿真.仿真结果表明,设计的控制器在执行效率和控制性能等方面具有突出的优势.     

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.     

基于双通道事件触发机制的水面无人艇同时故障检测与控制

本文研究双通道事件触发通讯机制下水面无人艇(USV)的同时故障检测和控制(SFDC)问题.考虑执行器故障和外部扰动,建立了SFDC框架以同时实现控制和故障检测目标.为了节约有限的通信资源和系统能源,在传感器–控制器通道和控制器–执行器通道分别部署了积分型事件触发器.在事件触发的通讯机制下,提出了故障检测器和控制器的联合设计准则.最后, USV的仿真结果验证了提出的基于事件触发的SFDC方法的有效性.     

复杂环境下多无人机协作式地面移动目标跟踪

针对多无人机(UAV)协同地面移动目标跟踪问题展开研究.提出一种基于主动感知的问题求解框架,建立多UAV协同目标跟踪问题模型;在此基础上,采用分布式无色信息滤波实现目标状态融合估计与预测;然后,基于预测目标状态,结合滚动时域控制与遗传算法设计一种多UAV在线协同航迹规划算法.仿真结果表明:结合预测目标状态在线优化UAV...     

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.     

Flocking control of a fleet of unmanned aerial vehicles

Current applications using single unmanned vehicle have been gradually extended to multiple ones due to their increased efficiency in mission accomplishment, expanded coverage areas and ranges, as well as enhanced system reliability. This paper presents a flocking control method with application to a fleet of unmanned quadrotor helicopters (UQHs). Three critical characteristics of formation keeping, collision avoidance, and velocity matching have been taken into account in the algorithm development to make it capable of accomplishing the desired objectives (like forest/pipeline surveillance) by safely and efficiently operating a group of UQHs. To achieve these, three layered system design philosophy is considered in this study. The first layer is the flocking controller which is designed based on the kinematics of UQH. The modified Cucker and Smale model is used for guaranteeing the convergence of UQHs to flocking, while a repelling force between each two UQHs is also added for ensuring a specified safety distance. The second layer is the motion controller which is devised based on the kinetics of UQH by employing the augmented state-feedback control approach to greatly minimize the steady-state error. The last layer is the UQH system along with its actuators. Two primary contributions have been made in this work: first, different from most of the existing works conducted on agents with double integrator dynamics, a new flocking control algorithm has been designed and implemented on a group of UQHs with nonlinear dynamics. Furthermore, the constraint of fixed neighbouring distance in formation has been relaxed expecting to significantly reduce the complexity caused by the increase of agents number and provide more flexibility to the formation control. Extensive numerical simulations on a group of UQH nonlinear models have been carried out to verify the effectiveness of the proposed method.     

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.     

Model predictive and non-cooperative dynamic game fault recovery control strategies for a network of unmanned underwater vehicles

In this paper, the problem of control and fault recovery for a team of autonomous underwater vehicles in the presence of loss of effectiveness (LOE) actuator faults is addressed. Towards this end, two different fault recovery control strategies based on the model predictive control technique as well as the dynamic game theory are proposed and developed. Given the allowable information that can be exchanged among the agents, both centralised and semi-decentralised recovery control schemes are considered and their associated corresponding fault recovery strategies are developed. The proposed active fault recovery control strategies incorporate both the online inaccurate as well as delayed actuator fault estimates to reconfigure the nominal (healthy state) controllers. The effectiveness of the proposed semi-decentralised fault recovery control schemes is quantitatively investigated through extensive simulation case studies considering various LOE actuator fault severities in one or more unmanned vehicles as well as fault detection and isolation module imperfections such as fault estimation error and time delays in detecting the faults. The simulation results demonstrate and illustrate that our proposed semi-decentralised recovery control scheme can maintain acceptable degraded tracking and formation keeping performance of both the faulty and healthy agents in the team with lower computational and communication bandwidth requirements as well as lower or fairly close control effort cost as compared to the centralised control recovery scheme.     

动态事件触发的无人机非线性系统故障检测

本文在Hi/H1优化框架下, 研究基于动态事件触发的无人机非线性系统故障检测问题. 高空、长航时无人 机需要通过通信网络与地面站进行数据交互, 以实现故障检测等复杂功能. 为了充分利用有限的通信资源, 采用动 态事件触发机制决定是否将测量输入输出数据传送给故障检测模块, 若传输数据不满足触发条件则被丢弃, 因此, 故障检测性能不仅受到干扰和故障影响, 还受到非事件触发时刻数据与实际系统数据误差影响, 即事件触发传输误 差影响. 为此, 针对无人机非线性系统, 提出一种新的动态事件触发Hi/H1故障检测方法. 该方法可以在动态事件触 发条件下, 实现故障检测滤波器残差与事件传输误差完全解耦, 能够避免连续通信和Zeno现象. 在Hi/H1优化框架 下, 通过Riccati方程递归计算, 得到动态事件触发故障检测滤波器的最优解. 最后, 以无人机非线性姿态控制系统为 例, 验证所提方法的有效性和可行性.     

Robust fault and icing diagnosis in unmanned aerial vehicles using LPV interval observers

This paper proposes a linear parameter varying (LPV) interval unknown input observer for the robust fault diagnosis of actuator faults and ice accretion in unmanned aerial vehicles (UAVs) described by an uncertain model. The proposed interval observer evaluates the set of values for the state, which are compatible with the nominal fault‐free and icing‐free operation and can be designed in such a way that some information about the nature of the unknown inputs affecting the system can be obtained, thus allowing the diagnosis to be performed. The proposed strategy has several advantages. First, the LPV paradigm allows taking into account operating point variations. Second, the noise rejection properties are enhanced by the presence of the integral term. Third, the interval estimation property guarantees the absence of false alarms. Linear matrix inequality–based conditions for the analysis/design of these observers are provided in order to guarantee the interval estimation of the state and the boundedness of the estimation. The developed theory is supported by simulation results, obtained with the uncertain model of a Zagi Flying Wing UAV, which illustrate the strong appeal of the methodology for identifying correctly unexpected changes in the system dynamics due to actuator faults or icing.     

Sensor cascading fault estimation and control for hypersonic flight vehicles based on a multidimensional generalized observer

This study presents a sensor cascading fault estimation and fault‐tolerant control (FTC) for a nonlinear Takagi‐Sugeno fuzzy model of hypersonic flight vehicles. Sensor cascading faults indicate the occurrence of source fault will cause another fault and the interval between them is really short, which makes it difficult to handle them in succession. A novel multidimensional generalized observer is used to estimate faults by integrating constant offset and time‐varying gain faults. Then, a fault‐tolerant controller is used to solve system nonlinearity and sensor fault problems. The observer and controller satisfy the performance index and are robust to external disturbances. A sufficient condition for the existence of observer and controller is derived on the basis of Lyapunov theory. Simulation results indicate the effectiveness of the proposed fault estimation and FTC scheme.     

无人机非确定性等价自适应容错飞行控制

针对存在执行器复合故障的固定翼无人机跟踪控制问题,本文提出一种基于非确定性等价原理的自适应容错飞行控制策略.该策略能够有效地估计无人机纵向动态中执行器的失效及漂移故障,保证故障发生后闭环系统的最优性能指标.在自适应容错飞行控制设计中,通过引入辅助系统并动态调节因子,构造非确定性等价原理中偏微分方程的近似解,以简化自适应律设计复杂度.此外,借助Lyapunov稳定性分析方法,证明了在所设计的自适应容错控制器作用下闭环系统的稳定性.最后,仿真验证表明所设计的控制方法能够保证故障无人机的闭环系统性能.     

Fault‐tolerant formation control of multiple UAVs in the presence of actuator faults

In order to counteract actuator faults in formation flight of multiple unmanned aerial vehicles (UAVs), this paper presents a fault‐tolerant formation control (FTFC) design methodology, in which the reference generator and the finite‐time convergence of FTFC gains are explicitly considered. Feasible references in response to actuator faults can be generated by considering the health and mission conditions of an overall team of UAVs. Moreover, by applying an auxiliary integrated regressor matrix and vector method, FTFC gains can converge within a finite amount of time to facilitate the fault accommodation process. Thus, the negative effects resulting from failed actuators can be compensated by the healthy/redundant actuators in UAVs. Simulation studies of UAV formation flight are carried out to exemplify the effectiveness of this design approach. Copyright © 2015 John Wiley & Sons, Ltd.     

基于自适应观测器控制系统的快速故障调节

针对基于自适应观测器故障调节设计中的两个难点,即系统满足严格正实(SPR)条件与故障估计的准确性和快速性,首先引入适当的坐标变换,有效地放松了严格SPR条件,适用于一大类控制系统的故障诊断;其次,针对变换后的系统,提出一种快速故障估计的设计方法,明显改善了故障估计的性能;再次,基于故障估计值修正控制律以补偿故障所带来的影响,使故障调节后的系统稳定;最后通过仿真实验验证了该方法的有效性.     

A fault accommodation control for nonlinear systems

Based on the use of neural networks for representation of the dynamics of faults, an active fault accommodation control law is proposed that guarantees the closed-loop stability for a class of nonlinear systems with faults. An example of using the control design proposed demonstrates the efficiency of this law for a typical nonlinear system. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 10–18, January–February 2006.     

类脑智能技术在无人系统上的应用

随着人工智能与脑科学等前沿技术的迅速发展,无人系统智能化研究正逐渐成为当今世界强国重点关注的战略发展方向,研究与之相关的科学问题具有前瞻性、战略性和带动性.文章首先分析了无人系统的发展需求,提出了面向需求的若干关键问题,包括复杂环境与态势信息的感知与认知问题、整体效能最优的分布式任务决策问题、面向任务需求的路径实时规划问题、考虑高不确定环境的自学习控制问题、应对非预期情况的故障诊断及容错问题以及基于人机接口的人机交互问题;随后,系统阐述了类脑智能技术在解决这些问题上的国内外研究现状;最后,论述了无人系统类脑智能化发展中依然存在的问题及未来发展趋势.     

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.