无人机集群的微分平坦性与编队控制研究

本文研究了无人机集群的微分平坦性,给出了相对运动的微分平坦映射,并以此为基础设计了分布式编队控制器.运动规划方面,通过求解受约束的优化问题,实时生成期望编队轨迹和编队构型.运动控制方面,采用微分平坦映射将运动指令映射为每架无人机的期望状态和控制输入,而后利用局部误差反馈设计分布式编队控制器跟踪期望运动轨迹.针对群体运动的稳定性问题,本文运用李雅普诺夫稳定性理论证明了闭环系统的稳定性,给出了控制参数的选取条件.最后仿真验证了编队控制方法在未知环境下的运动控制效果.     

Distributed Containment Control of Networked Nonlinear Second-order Systems With Unknown Parameters

In this paper, we study the containment control problem for nonlinear second-order systems with unknown parameters and multiple stationary/dynamic leaders. The topologies that characterize the interaction among the leaders and the followers are directed graphs. Necessary and sufficient criteria which guarantee the control objectives are established for both stationary leaders (regulation case) and dynamic leaders (dynamic tracking case) based protocols. The final states of all the followers are exclusively determined by the initial values of the leaders and the topology structures. In the regulation case, all the followers converge into the convex hull spanned by the leaders, while in the dynamic tracking case, not only the positions of the followers converge into the convex hull but also the velocities of the followers converge into the velocity convex hull of the leaders. Finally, all the theoretical results are illustrated by numerical simulations.      

Distributed Containment Control for Nonlinear Multi‐Agent Systems with Time‐Delayed Protocol

In this paper, the containment control problem is considered for nonlinear multi‐agent systems with directed communication topology. Under the guidance of designed distributed communication protocols with/without previous state information, the followers are expected to converge to a dynamic convex hull spanned by multiple leaders. Two multi‐step algorithms are proposed to construct the corresponding protocols, the state feedback protocol and the delay‐coupled protocol, under which the containment control can be achieved asymptotically. Furthermore, it is found that the delay‐coupled protocol is rather sensitive to time delays. That is, real‐time tracking will become impossible by only using long‐dated previous state information. Finally, a numerical example is given to demonstrate the applicability and efficiency of the proposed schemes.     

Bounded‐Input Control of the Quadrotor Unmanned Aerial Vehicle: A Vision‐Based Approach

In this paper, a bounded‐input controller is designed for the quadrotor vertical take‐off and landing unmanned aerial vehicle (UAV). Visual information is used to localize the aircraft with respect to its environment and an image‐based visual servo scheme is developed to navigate the motion of it. The visual features are selected from perspective image moments and projected on a rotated image plane, which simplifies the controller design. The flow of the features is used as the linear velocity information, and the controller assumes angular velocity and attitude information available for feedback. To design the controller, the dynamics of the quadrotor are decoupled into two parts: translational dynamics and rotational dynamics. First visual data are used to design a bounded‐input controller for the translational dynamics, and then a saturated controller is designed for the rotational dynamics. The boundedness of the controller increases the chance of keeping the visual features in the field of view of the camera. Furthermore, the controllers also cope with the unknown depth of the image, and the external disturbances. The complete stability analysis of the overall system is presented to show that all states are bounded and the error signals converge to zero asymptotically. Simulation examples are provided in both nominal and perturbed conditions which show the effectiveness of the proposed theoretical results.     

Nonlinear Adaptive Close Formation Control of Unmanned Aerial Vehicles

This paper treats the question of formationflight control of multiple unmanned aerial vehicles (UAVs). Inclose formation the wing UAV motion is affected by the vortexof the adjacent lead aircraft. The forces produced by these vorticesare complex functions of the relative position coordinates ofthe UAVs. In this paper, these forces are treated as unknownfunctions. For simplicity, it is assumed that the UAVs have autopilotsfor heading-, altitude-, and Mach-hold in the inner loops. Anadaptive control law is derived for the position control of thewing aircraft based on a backstepping design technique. In theclosed-loop system, commanded separation trajectories are asymptoticallytracked by each wing aircraft while the lead UAV is maneuvering.It is seen that an overparametrization in the design is essentialfor the decentralization of the control system. These resultsare applied to formation flight control of two UAVs and simulationresults are obtained. These results show that the wing UAV followsprecisely the reference separation trajectories in spite of theuncertainties in the aerodynamic coefficients, while the leadaircraft maneuvers.     

基于强化迭代学习的分布式无人机编队控制研究

在无人机行驶过程中,基站主机所定义的队列信息会对与飞行器相关的转向行为造成一定的影响,故为保证无人机飞行器的稳定行驶状态,基于强化迭代学习对分布式无人机队列控制算法展开研究。计算强化学习函数的具体数值,通过迭代处理的方式,实现对迭代值概率系数的分布表示,完成强化迭代学习模型的设计。以此为基础,定义无人机队列拓扑结构,并求解信息迁移指标的具体数值,实现基于强化迭代学习的无人机队列信息迁移。在无人机队列控制器的配合下,建立分布式队列信息集合,并联合其中的队列数据样本,求解UAV控制参数。再根据行进队列建模条件,完善控制算法执行流程,完成基于强化迭代学习的分布式无人机队列控制方法的设计。实验结果表明,在强化迭代学习模型的影响下,无人机转向角始终保持在0°-90°的数值范围之内,表示飞行器按照基站主机所定义的队列信息行驶,能够始终保持较为稳定的运动状态,符合实际应用需求。     

无人机编队飞行视景仿真关键技术研究

针对真实无人机编队飞行实验成本及风险较高的问题,提出一种基于Vega的虚拟验证平台,以克服OpenGL等视景开发工具代码可移植性较差、执行效率较低等缺点。分析无人机编队飞行视景仿真的系统需求,采用Vega的三维模型驱动与MFC灵活控制相结合的方法,研究多机飞行中的协同机制、仿真数据通信、编队飞行的实时控制、显示、记录与回放等编队仿真技术。结果证明,该虚拟验证平台仿真度高、实时性好、可移植性强、数据传输可靠。     

Distributed Robust Containment Control of Linear Heterogeneous Multi-Agent Systems: An Output Regulation Approach

In this paper, we consider the robust output containment problem of linear heterogeneous multi-agent systems under fixed directed networks. A distributed dynamic observer based on the leaders’ measurable output was designed to estimate a convex combination of the leaders’ states. First, for the case of followers with identical state dimensions, distributed dynamic state and output feedback control laws were designed based on the state-coupled item and the internal model compensator to drive the uncertain followers into the leaders’ convex hull within the output regulation framework. Subsequently, we extended theoretical results to the case where followers have nonidentical state dimensions. By establishing virtual errors between the dynamic observer and followers, a new distributed dynamic output feedback control law was constructed using only the states of the compensator to solve the robust output containment problem. Finally, two numerical simulations verified the effectiveness of the designed schemes.      

带噪声多自主体的均方包容控制

考虑了带噪声的多自主体系统的包容控制问题. 由于噪声的存在, 我们引入了衰减增益法来抑制噪声. 在动态拓扑和随机切换拓扑下分别研究了包容控制问题, 并给出了保证均方收敛的通讯拓扑条件以及衰减增益条件. 最后给出了数值仿真来验证算法有效性.     

菱形翼布局无人机自抗扰直接升力着陆控制

针对采用传统的着陆控制方法时,菱形翼布局无人机存在着陆俯仰姿态角为负,对无人机着陆不利的情况,提出一种采用直接升力进行着陆的控制方案,可以实现着陆轨迹与着陆姿态之间的解耦,使得无人机可以以较好的姿态进行着陆.采用自抗扰控制(ADRC)方法分别设计了无人机非线性直接升力控制律以及着陆轨迹跟踪控制律.仿真结果表明:采用ADRC设计的非线性直接升力控制律可以实现直接升力控制的3种模式,并且对气动参数摄动具有较强的鲁棒性;采用直接升力着陆控制方法可以使得无人机以有利的姿态进行着陆,同时在近地面突风作用下,无人机依然可以以较好的姿态进行着陆.     

Distributed MPC for Tracking and Formation of Homogeneous Multi‐agent System with Time‐Varying Communication Topology

The distributed model predictive control (MPC) is studied for the tracking and formation problem of multi‐agent system with time‐varying communication topology. At each sampling instant, each agent solves an optimization problem respecting input and state constraints, to obtain its optimal control input. In the cost function for the optimization problem of each agent, the formation weighting coefficient is properly updated so that the adverse effect of the time‐varying communication topology on the closed‐loop stability can be counteracted. It is shown that the overall multi‐agent system can achieve the desired tracking and formation objectives. The effectiveness of the results is demonstrated through two examples.     

Unmanned Aerial Vehicles Formation Using Learning Based Model Predictive Control

This paper presents a solution for the formation flight problem for multiple unmanned aerial vehicles (UAVs) cooperating to execute a required mission. Learning Based Model Predictive Control (LBMPC) is implemented on the team of UAVs in order to accomplish the required formation. All flight simulations respect Reynold's rules of flocking to avoid UAV collisions with nearby flockmates, match the team members velocity and stay close to each other during the formation. The main contribution of this paper lies in the application of LBMPC to solve the problem of formation for an autonomous team of UAVs. The proposed solution is theoretically, by the application of analysis to the problem, demonstrated to be stable. Moreover, simulations support the findings of the paper. The main contributions of this paper are the proposed LBMPC formulation for formation of vehicles with uncertainty in their models, and the theoretical analysis of the solution.     

Containment Control of Fractional Order Multi-Agent Systems With Time Delays

In complex environments, many distributed multiagent systems are described with the fractional-order dynamics. In this paper, containment control of fractional-order multiagent systems with multiple leader agents are studied. Firstly, the collaborative control of fractional-order multi-agent systems (FOMAS) with multiple leaders is analyzed in a directed network without delays. Then, by using Laplace transform and frequency domain theorem, containment consensus of networked FOMAS with time delays is investigated in an undirected network, and a critical value of delays is obtained to ensure the containment consensus of FOMAS. Finally, numerical simulations are shown to verify the results.      

带有不匹配干扰的二阶多自主体系统有限时间包容控制

针对多自主体系统群集运动问题,本文研究了带有不匹配干扰的二阶系统有限时间包容控制.运用现代控制理论,设计了非线性观测器,对系统未知状态和干扰进行估计.在状态估计的基础上,构建了基于干扰观测器的多自主体系统的协同控制算法.应用代数图论和齐次性理论等方法,分析了二阶多自主体系统有限时间包容控制.数据仿真中应用基于观测器的包容控制算法,使得系统的运动状态最终都收敛到由多个领导者所围成的目标区域中,验证了本文结果的有效性.     

无人机飞行控制系统模拟器设计

提出了一种基于工业控制计算机开发的某型无人机飞行控制系统模拟器设计;详细介绍了系统设计原理，给出了硬件构成方案、软件功能模块组成和程序流程图，最后分析了测试结果；该模拟器充分利用了当前计算机技术、自动控制技术、系统实时仿真技术和面向对象编程技术，具有功能强大、界面友好、操作灵活的特点。可用于无人机系统先期设计验证或后期测试维护；实际使用情况表明该系统性能良好，完全能够代替真实飞行控制系统进行实时仿真试验。     

微小型四旋翼无人飞行器姿态控制

关于自主研发的微小型四旋翼无人飞行器姿态控制问题,针对姿态控制要求的稳定性,根据飞行器的飞行原理,通过数学推导建立近似的姿态角线性模型.操作飞行器飞行并采集相关飞行数据在MATLAB中辨识出有效的模型参数并验证模型准确性.在姿态角模型的基础上,分别设计了ALQR控制器以及卡尔曼滤波器.飞行实验结果表明,设计的卡尔曼滤波器具有很好的滤波效果和状态量推测性能,设计的ALQR控制器能较好的解决控制指令跟踪的问题,满足姿态优化控制的要求.     

基于近似模拟的多智能体系统分布式层次控制设计

本文主要探讨基于近似模拟的多智能体系统分布式层次控制的设计问题。为降低问题复杂度,首先建立了一个简单的抽象系统指导各智能体,继而讨论这一抽象系统和多智能体之间的模拟关系。借助于该抽象系统,给出多智能体系统完成一类协调任务的分布式层次控制器。同时利用模拟函数和共同Lyapunov函数,进一步分析了多个体系统在切换拓扑下的集体行为。     

Boundary and Distributed Control for a Nonlinear Three‐Dimensional Euler‐Bernoulli Beam Based On Infinite Dimensional Disturbance Observer

Control problems in spatially distributed systems are challenging because the disturbance is of infinite dimensions. To this end, this paper discusses an infinite dimensional disturbance observer design, which is illustrated based on a partial differential equation (PDE) model of a nonlinear three‐dimensional Euler‐Bernoulli beam. The basic idea of the observer design is to modify the estimations based on the difference between the estimated output and actual output. Moreover, an auxiliary parameter system is established to help with the analysis. Then a Lyapunov function candidate consisting of the energy of the system, the observer error and an auxiliary term is given. After a series of analyses of the function, distributed controllers and boundary controllers based on the proposed observer are given to restrain vibration. Finally, by numerical simulations, the convergence of the observer is demonstrated, and the efficacy of control performance is also shown.     

无人机吊挂飞行系统的减摆控制设计

主要考虑了四旋翼无人机（Unmanned aerial vehicle,UAV）吊挂飞行系统的位置控制及负载摆动抑制的设计问题.在存在欠驱动特性以及未知系统参数的约束下,本文基于能量法设计了一种非线性控制策略,实现了对无人机位置的精确控制和飞行过程中负载摆动的快速抑制.基于Lyapunov方法的稳定性分析证明了闭环系统的稳定性,位置误差的收敛及摆动的抑制.实验结果表明本文提出的控制策略取得了较好的控制效果.     

Distributed Fault-Tolerant Containment Control for Nonlinear Multi-Agent Systems Under Directed Network Topology via Hierarchical Approach

This paper investigates the distributed fault-tolerant containment control(FTCC)problem of nonlinear multi-agent systems(MASs)under a directed network topology.The proposed control framework which is independent on the global information about the communication topology consists of two layers.Different from most existing distributed fault-tolerant control(FTC)protocols where the fault in one agent may propagate over network,the developed control method can eliminate the phenomenon of fault propagation.Based on the hierarchical control strategy,the FTCC problem with a directed graph can be simplified to the distributed containment control of the upper layer and the fault-tolerant tracking control of the lower layer.Finally,simulation results are given to demonstrate the effectiveness of the proposed control protocol.