Robust Tracking Control of Uncertain MIMO Nonlinear Systems with Application to UAVs

In this paper, we consider the robust adaptive tracking control of uncertain multi-input and multi-output(MIMO) nonlinear systems with input saturation and unknown external disturbance. The nonlinear disturbance observer(NDO)is employed to tackle the system uncertainty as well as the external disturbance. To handle the input saturation, an auxiliary system is constructed as a saturation compensator. By using the backstepping technique and the dynamic surface method,a robust adaptive tracking control scheme is developed. The closed-loop system is proved to be uniformly ultimately bounded thorough Lyapunov stability analysis. Simulation results with application to an unmanned aerial vehicle(UAV) demonstrate the effectiveness of the proposed robust control scheme.

Small unmanned helicopter's attitude controller by an on-line adaptive fuzzy control system

Since small unmanned helicopter flight attitude control process has strong time-varying characteristics and there are random disturbances,the conventional control methods with unchanged parameters are often unworkable.An on-line adaptive fuzzy control system(AFCS)was designed,in a way that does not depend on a process model of the plant or its approximation in the form of a Jacobian matrix.Neither is it necessary to know the desired response at each instant of time.AFCS implement a simultaneous on-line tuning of fuzzy rules and output scale of fuzzy control system.The two cascade controller design with an inner(attitude controller)and outer controller(navigation controller)of the small unmanned helicopter was proposed.At last,an attitude controller based on AFCS was implemented.The flight experiment showed that the proposed fuzzy logic controller provides quicker response,smaller overshoot,higher precision,robustness and adaptive ability.It satisfies the needs of autonomous flight.

Asynchronous H_∞ Control for Unmanned Aerial Vehicles: Switched Polytopic System Approach

This study is concerned with the H∞control for the full-envelope unmanned aerial vehicles(UAVs) in the presence of missing measurements and external disturbances. With the dramatic parameter variations in large flight envelope and the locally overlapped switching laws in flight, the system dynamics is modeled as a locally overlapped switched polytopic system to reduce designing conservatism and solving complexity. Then,considering updating lags of controller s switching signals and the weighted coefficients of the polytopic subsystems induced by missing measurements, an asynchronous H∞control method is proposed such that the system is stable and a desired disturbance attenuation level is satisfied. Furthermore, the sufficient existing conditions of the desired switched parameter-dependent H∞controller are derived in the form of linear matrix inequality(LMIs) by combining the switched parameter-dependent Lyapunov function method and average dwell time method.Finally, a numerical example based on a highly maneuverable technology(Hi MAT) vehicle is given to verify the validity of the proposed method.

Quadcopter UAV Modeling and Automatic Flight Control Design

The mathematical model of quadcopter-unmanned aerial vehicle(UAV)is derived by using two approaches:One is the Newton-Euler approach which is formulated using classical mechanics;and other is the Euler-Lagrange approach which describes the model in terms of kinetic(translational and rotational)and potential energy.The proposed quadcopter′s non-linear model is incorporated with aero-dynamical forces generated by air resistance,which helps aircraft to exhibits more realistic behavior while hovering.Based on the obtained model,the suitable control strategy is developed,under which two effective flight control systems are developed.Each control system is created by cascading the proportional-derivative(PD)and T-S fuzzy controllers that are equipped with six and twelve feedback signals individually respectively to ensure better tracking,stabilization,and response.Both proposed flight control designs are then implemented with the quadcopter model respectively and multitudinous simulations are conducted using MATLAB/Simulink to analyze the tracking performance of the quadcopter model at various reference inputs and trajectories.

基于KNN神经网络的无人机作业操控系统研究

为进一步提升我国农业植保无人机的精准作业效率,针对其操控系统展开优化研究。选定KNN神经网络算法为执行理念,以无人机作业控制原理为基础,搭建正确的过程参数动态计算模型,进行操控系统的算法实现与调控配置,并展开基于KNN神经网络的无人机喷施作业试验。试验结果表明:KNN神经网络算法下的无人机操控系统运行稳定,过程参数的分类准确率相对提高了8.00%,目标喷施流量与试验喷施流量的偏差率相对降低了5.71%,农药喷施均匀度可提升至94.75%,整机作业综合效率明显提升。此设计理念以计算机智能数据处理为出发点,对无人机的高效率全面发挥有一定的推动作用,可用于类似智能农机装备的控制系统改进与开发,具有一定的参考价值。

Observer-based backstepping longitudinal control for carrier-based UAV with actuator faults

The paper presents the longitudinal control for the carrier-based unmanned aerial vehicle (UAV) system with unmeasured states, actuator faults, control input constraints, and external disturbances. By combining output state observer, adaptive fuzzy control, and constraint backstepping technology, a robust fault tolerant control approach is proposed. An output state observer with fuzzy logic systems is developed to estimate unmeasured states, and command filters rather than differentiations of virtual control law are used to solve the computational complexity problem in traditional backstepping. Additionally, a robust term is introduced to offset the fuzzy adaptive estimation error and external disturbance, and an appropriate fault controller structure with matching conditions obtained from fault compensation is proposed. Based on the Lyapunov theory, the designed control program is illustrated to guarantee that all the closed-loop signals of the given system are bounded, and the output errors converge to a small neighborhood of zero. A carrier-based UAV nonlinear longitudinal model is employed to testify the feasibility and validity of the control scheme. The simulation results show that all the controllers can perform at a satisfactory level of reference tracking despite the existence of unknown aerodynamic parameters and actuator faults. ? 2017 Beijing Institute of Aerospace Information.

事件触发的时滞二阶多UAV系统一致性控制

研究具有固定输入时滞的二阶多无人机系统在事件触发下进行不完全随机采样,并达到一致性控制的问题。提出一种阈值依赖于多无人机系统事件触发时刻和初始状态的事件触发机制,并给出在此事件触发机制下具有固定输入时滞二阶多无人机系统的分布式控制策略。当无人机自身状态变化量满足触发条件时,无人机间进行信息交互,控制器根据此次事件触发的采样状态值进行控制输入更新。通过理论推理证明一致性控制的结论。最后,通过仿真验证了算法的有效性。

基于ARM+CPLD的UAV飞行控制系统设计

根据UAV飞行控制系统的功能任务要求,提出了一种以ARM为控制核心、以CPLD为辅助控制器件的飞行控制方案。描述了飞行控制系统总体设计方案,详细设计了飞控计算机的硬件和软件。为提高飞控系统的运算速度和精度,系统硬件采用ARM＋CPLD模块设计,二者通过双口RAM进行数据交换;为满足飞控系统实时性和稳定性的要求,系统移植了μC/OS-Ⅱ实时操作系统,并根据控制功能将应用程序划分为7个任务。最后,为验证系统设计的可行性,将仿真数据和试飞数据进行了对比分析,结果表明系统设计正确、可行。

无人机在乡村振兴精准农业中的应用研究——基于汉语语言多维视角选择

介绍了汉语语言多维视角选择在无人机中的应用,设计了无人机飞行控制系统整体方案,并从姿态检测和高度检测等模块设计了无人机飞行控制系统硬件部分,最后建立了无人机运动模型和实现了无人机自主飞行的避障策略。飞行试验结果表明:无人机可以准确从起点飞行至终点,中途避开了障碍物,具有较好的稳定性,验证了飞行避障策略的可行性。

跨介质无人机的技术问题与解决方案分析

阐述跨介质无人机作为一种能够在不同介质(水体、空气)中自由切换的多功能飞行器,受到广泛关注。分析跨介质无人机所面临的机械结构、能源与动力系统、导航与控制系统方面的技术问题,提出相应解决方案。通过优化机械结构、改进能源系统和升级导航控制系统的措施,有效地解决跨介质无人机的技术挑战,推动其在各个应用领域的发展。

全驱动倾转四旋翼式飞枪的建模与控制

欠驱动的机/枪一体式四旋翼飞枪位置和姿态的控制存在耦合,无法实现带俯仰角的悬停射击,移动射击过程中火控策略复杂。设计了一种全驱动的倾转四旋翼无人机,并以此作为飞枪载体,在实现系统解耦的同时,简化了控制分配方法。首先通过牛顿欧拉法对系统进行数学建模,然后利用反步法设计控制器并证明系统稳定性,最后通过Simulink进行仿真实验。实验结果表明:本文设计的全驱动飞枪模型可实现位置和姿态的解耦控制,跟踪误差小,可满足飞枪悬停射击、移动射击的射击要求,适用于实时性要求高的飞/火控系统。

未知干扰下四旋翼无人机群固定时间编队控制

在未知干扰条件下,针对欠驱动、非线性的四旋翼无人机群编队控制问题,提出了一种抗干扰的固定时间编队控制方法。首先,设计分布式固定时间滑模估计器,在仅有部分无人机获取到期望轨迹的条件下,每架无人机都能快速估计出自己的期望位置信息。其次,引入固定时间干扰观测器用于估计未知的复合干扰,使无人机能够生成干扰估计值以抵消复合干扰对其带来的影响。然后,在无人机的位置层与控制层设计固定时间滑模控制器,实现对期望轨迹的跟踪,所给出的方法能够满足姿态稳定收敛。最后,数值仿真验证了所提出方法的有效性。

基于Pixhawk飞控的硬件在环仿真系统设计

Pixhawk飞控在民用无人机(UAV)领域得到广泛应用。为了在Pixhawk飞控上实现硬件在环仿真功能以达到验证飞控飞行性能的目的,设计了基于Pixhawk飞控的四旋翼无人机硬件在环仿真系统。通过构建四旋翼机体模型,实现模型在电机转速信号的驱动下输出位姿数据;位姿数据传输到飞控并重构为模拟传感器数据,飞控内核对传感器数据处理后输出电机转速信号驱动模型飞行,由此构成飞控硬件在环的仿真环路。在测试中使用相同航线进行了仿真飞行与真实飞行,并计算2种飞行模式数据的相关系数,系数普遍高于0.85,表明获得了较为逼真的仿真效果。

国内外无人机系统研究进展及应用

随着人工智能和无人机(Unmanned Aerial Vehicle,UAV)技术的深度融合,UAV已成为现代战争中的一把利器,各大军事强国均在竞相研发,力求在未来战争中占据制高点。概述了美国、中国、俄罗斯、英国和以色列等军事强国正在发展的UAV系统现状,总结了其最新研究进展和典型成果;在此基础上,从6个不同方面介绍了UAV系统作战所需的关键技术,并结合近年多场局部冲突中的UAV实战应用,梳理了其典型应用场景。旨在为UAV技术发展以及应用落地提供参考。

无人机地面控制站通用化研究

无人机地面控制站作为无人机系统的信息汇聚中心和指挥控制中心,是保障飞行安全、遂行作战任务和共享侦察载荷信息的关键,同时也是无人机与其他作战力量实现互联互通的重要手段。目前不同的飞机平台单位、甚至相同单位不同的团队设计的地面控制站也无法通用,文中通过分析目前地面控制站现状,构建通用地面控制站型谱,建立通用化标准体系,设计系统和软件体系架构,提出无人机通用地面控制站关键技术解决方案。

多UAV集结任务的分布式协同与优化控制

基于一致性理论的多无人机分布式协同控制已广泛运用于无人机作战中,通过一致性控制算法实现状态一致完成协同需求。建立了集结问题的数学模型,基于协调变量和协调函数的分解策略进行求解。为实现协同控制的最优性,改进了平均一致性控制算法,采用Hamilton-Jacobi-Bellman方程给出基本优化一致性控制算法。在控制算法中引入过去状态差值,提高控制算法的动态响应性和能量最优性;同时采用遗传算法优化代价函数的加权矩阵,进一步提高控制算法的动态响应性和能量最优性,缩短了任务执行时间。理论分析和仿真实验验证了方法的有效性和可行性。

基于AVR单片机的UAV飞行控制系统

GPS模块作为飞机方位探测器,利用温度补偿技术设计了具有较高分辨率的气压高度检测器。介绍了三轴姿态传感器MMA7260Q、陀螺仪、相应的接口电路和数字式滤波器;给出了电池电量测量电路以及字符叠加器MAX7456的应用技术。

快速一致性控制算法下的多UAV分布式协同控制

多无人机系统中,系统状态的一致性是实现多无人机分布式协同控制的基础,一致性控制算法是多无人机系统实现状态一致的有效方法。通信约束条件下,无人机平台基于局部交互信息,通过一致性控制算法,控制系统状态演化一致。为解决改变通信拓扑结构和多跳路由通信的不可操作性问题,引入状态差值和预测状态,设计新的快速一致性控制算法。给出新算法收敛性和快速性的相关定理,并进行了严格的数学证明,在分布式协同控制结构下实现多无人机快速任务协同。理论分析和仿真实验验证了算法的可行性和有效性。

Neural Network Based Feedback Linearization Control of an Unmanned Aerial Vehicle

This paper presents a flight control design for an unmanned aerial vehicle （UAV） using a nonlinear autoregressive moving average （NARMA-L2） neural network based feedback linearization and output redefinition technique. The UAV investigated is non- minimum phase. The output redefinition technique is used in such a way that the resulting system to be inverted is a minimum phase system. The NARMA-L2 neural network is trained off-line for forward dynamics of the UAV model with redefined output and is then inverted to force the real output to approximately track a command input. Simulation results show that the proposed approaches have good performance.

小型固定翼UAV飞控系统的嵌入式设计

随着小型无人机飞控任务的日趋复杂,传统低性能飞控系统已不能满足需要,对此本文提出一种基于ARM-Linux结构的飞控系统的嵌入式设计方法。设计了基于高性能低功耗嵌入式处理器ARM Cortex-A9芯片IMX6Q的嵌入式飞控系统的硬件设计,该系统集成了9轴MIMU、高度计、空速计和GPS等多种传感器。分析了基于嵌入式Linux的飞控软件开发流程,阐述了移植Linux内核的步骤及基于嵌入式Linux设计的多进程飞行控制软件。最后,通过手控飞行验证了硬件平台的可行性和软件设计方法的合理性。采用嵌入式方法设计飞控系统,使飞控系统具备多任务调度、可移植性好、易于二次开发等特点。