无人飞行器综合检测控制系统

分析了无人飞行器系统构成,对其综合检测控制系统功能和实现技术进行了分析和研究,探讨了通用化无人飞行器检测控制系统方案,针对具体无人机系统进行了设计和实现,实际应用表明本方案具有通用必和很强的工程实用性。     

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。     

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.     

A Software-in-the-Loop Implementation of Adaptive Formation Control for Fixed-Wing UAVs

This paper discusses the design and software-in-the-loop implementation of adaptive formation controllers for fixed-wing unmanned aerial vehicles (UAVs) with parametric uncertainty in their structure, namely uncertain mass and inertia. In fact, when aiming at autonomous flight, such parameters cannot assumed to be known as they might vary during the mission (e.g. depending on the payload). Modeling and autopilot design for such autonomous fixed-wing UAVs are presented. The modeling is implemented in Matlab, while the autopilot is based on ArduPilot, a popular open-source autopilot suite. Specifically, the ArduPilot functionalities are emulated in Matlab according to the Ardupilot documentation and code, which allows us to perform software-in-the-loop simulations of teams of UAVs embedded with actual autopilot protocols. An overview of realtime path planning, trajectory tracking and formation control resulting from the proposed platform is given. The software-inthe-loop simulations show the capability of achieving different UAV formations while handling uncertain mass and inertia.      

Performance Comparison of Controllers with Fault-Dependent Control Allocation for UAVs

This paper combines fault-dependent control allocation with three different control schemes to obtain fault tolerance in the longitudinal control of unmanned aerial vehicles. The paper shows that fault-dependent control allocation is able to accommodate actuator faults that would otherwise be critical and it makes a performance assessment for the different control algorithms: an \(\mathcal {L}_{1}\) adaptive backstepping controller; a robust sliding mode controller; and a standard PID controller. The actuator faults considered are the partial to total loss of the elevator, which is a critical component for the safe operation of unmanned aerial vehicles. During nominal operation, only the main actuator, namely the elevator, is active for pitch control. In the event of a partial or total loss of the elevator, fault-dependent control allocation is used to redistribute control to available healthy actuators. Using simulations of a Cessna 182 aircraft model, controller performance and robustness are evaluated by metrics that assess control accuracy and energy use. System uncertainties are investigated over an envelope of pertinent variation, showing that sliding mode and \(\mathcal {L}_{1}\) adaptive backstepping provide robustness, where PID control falls short. Additionally, a key finding is that the fault-dependent control allocation is instrumental when handling actuator faults.     

四旋翼无人机参数预测和抗扰动自适应轨迹跟踪控制

为了降低外界环境对四旋翼无人机飞行轨迹的扰动性,提高无人机的控制精度,提出1种基于滑模控制的四旋翼无人机参数预测和抗扰动的自适应轨迹跟踪控制器。这种控制器对四旋翼无人机系统的不确定状态参数、气流、风阻和执行器故障等外界扰动进行预测,实现了对系统输入的状态补偿和扰动补偿,提高了无人机的轨迹跟踪效率和抗扰动能力,消除了机体在飞行过程中的抖振现象,提高了无人机系统对环境的适应性和控制器的稳定性。通过仿真实验,分析了四旋翼无人机在不同控制器作用下的轨迹跟踪性能曲线,验证了所提出的控制器的优越性和有效性。     

Linear Quadratic Control for Quadrotors UAVs Dynamics and Formation Flight

Cooperative control of Unmanned Aerial Vehicles (UAVs) is currently being researched for a wide range of applications. Applicability of aerial unmanned systems might be increased by formation flight. After a necessary overview of quadrotor flight dynamics and linear quadratic control fundamentals, this control technique is applied to the full quadrotor dynamics. Then the more recent and challenging neural networks based control strategy is introduced from a theoretical perspective and applied to the quadrotor vertical dynamics; the results are compared with the relevant linear quadratic controlled behaviour. Finally, based on the developed single-quadrotor control architectures, a practical leader-follower formation concept is simulated, both for the linear quadratic and the neural networks based approach.     

Cooperative Control of UAVs for Localization of Intermittently Emitting Mobile Targets

Compared with a single platform, cooperative autonomous unmanned aerial vehicles (UAVs) offer efficiency and robustness in performing complex tasks. Focusing on ground mobile targets that intermittently emit radio frequency signals, this paper presents a decentralized control architecture for multiple UAVs, equipped only with rudimentary sensors, to search, detect, and locate targets over large areas. The proposed architecture has in its core a decision logic which governs the state of operation for each UAV based on sensor readings and communicated data. To support the findings, extensive simulation results are presented, focusing primarily on two success measures that the UAVs seek to minimize: overall time to search for a group of targets and the final target localization error achieved. The results of the simulations have provided support for hardware flight tests.      

一种持续侦察无人机集群规模自适应调控方法

无人机集群(unmanned aerial vehicles, UAVs)持续侦察是多无人机协同控制中一个重要的研究方向.随着任务环境和使命需求越来越复杂,对无人机集群可重构性和柔性的要求也越来越高.其中,对于自适应可重构无人机集群,无人机的规模数量是最基本的控制要素之一.然而,目前大部分无人机集群的研究都侧重于特定任务背景下的路径规划,而集群规模的动态调整则未被考虑.针对传统无人机集群侦察设计中,集群的数量难以自适应调整以匹配不同侦察环境、不同侦察态势的问题,提出了基于区域信息熵的“数字草皮”及其植物量变化模型,模仿草皮-食草动物生态系统中的动态平衡机制,设计了目标区域-无人机集群持续侦察体系中的规模控制方法.在此基础上,研究了侦察体系达到稳定时群落矩阵和平衡点的情况,探讨了在不同任务环境中、不同效能约束限制下,无人机集群规模的自适应调控方法,并利用仿真和可视化手段对平衡点的存在性和系统的收敛性进行了验证.     

无人机导航监控系统设计与实现

针对传统模拟表盘式导航监控系统存在人工估算飞机位置偏差大、模拟表盘读数精度低、人机交互性差等问题,提出了基于数字地图、信号滤波处理和自动航线规划的无人机导航监控系统设计方案,给出了设计原理、系统组成以及实现方法.     

无人机航迹预见控制及其仿真研究

为了最大限度地发挥无人机的性能,机动快速地配合其它兵种作战,需要无人机在其有效使用范围内发挥其应有的潜力,在这方面飞行控制系统的性能起着决定性的作用。本文在对目前无人机航迹控制技术存在问题进行分析的基础上,利用数字预见控制的理论和方法设计控制算法作为航迹优化措施,优化无人机的飞行控制性能,提高其机动性和快速反应能力。仿真结果表明了该算法的有效性。     

变载荷下六旋翼无人机高度控制

六旋翼无人机应用于植保领域时通常需要定高飞行,单一机载微传感器无法长时间准确的跟踪六旋翼无人机的高度,且当负载发生变化时无人机的高度控制会出现不稳定现象.针对上述问题,本文采用了一种基于气压计和加速度计卡尔曼滤波融合的高度测量系统,并设计了一个双闭环PID控制加前馈控制的高度控制器,最终获得了无人机飞行高度的精确估计与稳定控制.实验结果表明,经过卡尔曼滤波可以得到准确、平稳的高度值和速度值.提出的高度控制器在变载荷情况下也能很好的控制无人机的高度.     

Predicting Controller Capacity in Supervisory Control of Multiple UAVs

In the future vision of allowing a single operator to remotely control multiple unmanned vehicles, it is not well understood what cognitive constraints limit the number of vehicles and related tasks that a single operator can manage. This paper illustrates that, when predicting the number of unmanned aerial vehicles (UAVs) that a single operator can control, it is important to model the sources of wait times (WTs) caused by human-vehicle interaction, particularly since these times could potentially lead to a system failure. Specifically, these sources of vehicle WTs include cognitive reorientation and interaction WT (WTI), queues for multiple-vehicle interactions, and loss of situation awareness (SA) WTs. When WTs were included, predictions using a multiple homogeneous and independent UAV simulation dropped by up to 67%, with a loss of SA as the primary source of WT delays. Moreover, this paper demonstrated that even in a highly automated management-by-exception system, which should alleviate queuing and WTIs, operator capacity is still affected by the SA WT, causing a 36% decrease over the capacity model with no WT included.     

Decentralised Standoff Tracking of Moving Targets Using Adaptive Sliding Mode Control for UAVs

This paper proposes a decentralised vector field guidance algorithm for coordinated standoff tracking of a ground moving target by multiple UAVs. In particular, this study introduces additional adaptive terms in an existing sliding mode control concept for standoff tracking guidance, in order to reduce the effect of unmodelled dynamics and disturbances. Decentralised angular separation control between UAVs, in conjunction with decentralised estimation, is also introduced using either velocity or orbit radius change by different information/communication structures. Numerical simulations are performed to verify the feasibility and benefits of the proposed approach under a realistic ground vehicle tracking scenario, using multiple UAVs having unknown parameters in the heading-hold autopilot.     

Decentralized Guidance Control of UAVs with Explicit Optimization of Communication

We design a decentralized guidance control method for autonomous unmanned aerial vehicles (UAVs) tracking multiple targets. We formulate this guidance control problem as a decentralized partially observable Markov decision process (Dec-POMDP). As in the case of partially observable Markov decision process (POMDP), it is intractable to solve a Dec-POMDP exactly. So, we extend a POMDP approximation method called nominal belief-state optimization (NBO) to solve our control problem posed as a Dec-POMDP. We incorporate the cost of communication into the objective function of the Dec-POMDP, i.e., we explicitly optimize the communication among the UAVs at the network level along with the kinematic control commands for the UAVs. We measure the performance of our method with the following metrics: 1) average target-location error, and 2) average communication cost. The goal to maximize the performance with respect to each of the above metrics conflict with each other, and we show through empirical study how to trade off between these performance metrics using a scalar parameter. The NBO method induces coordination among the UAVs even though the system is decentralized. To demonstrate the effectiveness of this coordination, we compare our Dec-POMDP approach with a greedy approach (a noncooperative approach), where the UAVs do not communicate with each other and each UAV optimizes only its local kinematic controls. Furthermore, we compare the performance of our approach of optimizing the communication between the UAVs with a fixed communication scheme—where only the UAV kinematic controls are optimized with an underlying fixed (non-optimized) communication scheme.     

基于故障观测器的多无人机姿态一致性控制

在多个固定翼无人机姿态主从式一致性控制过程中,给出单个固定翼无人机在理想情况下的姿态动力学模型,即名义模型.考虑到无人机在实际运行过程中存在的外部干扰、状态测量误差、控制器微小故障以及无人机实际模型与名义模型之间的偏移,提出一种基于观测器和神经网络的故障检测方法,以实时检测出无人机中存在的故障、模型不确定以及干扰情况....     

无人机车载起飞飞控软件设计及仿真

关于无人机起飞优化控制软件设计问题,由于无人机车载起飞要求高度迅速升高、速度迅速增大的特点,对无人机俯仰角回路和速度回路进行PID设计.并根据车载起飞速度和高度的要求,将飞控软件划分为四个控制阶段,详细设计了飞控软件的控制流程.通过数字仿真,验证了预偏补偿对无人机姿态控制的重要性;通过半物理仿真,验证了车载起飞的设计已经达到了预定的要求,改善了车载起飞的飞行品质.基于以上分析,无人机车载起飞效果良好,对同类型的无人机具有一定的参考价值.     

Vision Based Control for Fixed Wing UAVs Inspecting Locally Linear Infrastructure Using Skid-to-Turn Maneuvers

The following paper proposes a novel application of Skid-to-Turn maneuvers for fixed wing Unmanned Aerial Vehicles (UAVs) inspecting locally linear infrastructure. Fixed wing UAVs, following the design of manned aircraft, commonly employ Bank-to-Turn maneuvers to change heading and thus direction of travel. Whilst effective, banking an aircraft during the inspection of ground based features hinders data collection, with body fixed sensors angled away from the direction of turn and a panning motion induced through roll rate that can reduce data quality. By adopting Skid-to-Turn maneuvers, the aircraft can change heading whilst maintaining wings level flight, thus allowing body fixed sensors to maintain a downward facing orientation. An Image-Based Visual Servo controller is developed to directly control the position of features as captured by onboard inspection sensors. This improves on the indirect approach taken by other tracking controllers where a course over ground directly above the feature is assumed to capture it centered in the field of view. Performance of the proposed controller is compared against that of a Bank-to-Turn tracking controller driven by GPS derived cross track error in a simulation environment developed to replicate the field of view of a body fixed camera.