基于扩张鸽群优化的舰载无人机横侧向着舰自主控制

舰载无人机着舰会受到舰尾流、航母甲板运动的干扰.为加快无人机在着舰时横侧向响应以及提高舰载机着舰对干扰的鲁棒性,本文提出了一种基于扩张鸽群优化算法的显式模型预测控制方法,并将其应用于舰载机姿态控制器设计,用于解决所设计控制器的参数优化问题.与基本鸽群优化算法、粒子群算法的仿真对比实验表明,相比传统智能优化算法,本文所提...     

基于TECS/H_∞的无人机侧向着舰技术研究

研究无人机侧向着舰优化控制问题,由于外部环境恶劣,造成干扰,影响安全降落。针对传统控制方法无法抑制侧风干扰和浪费能量的问题,为抑制侧风干扰并且充分利用无人机自身的能量,提高着舰精度,运用总能量控制系统(TECS)建立了无人机侧向自动着舰系统,设计了H∞输出反馈控制器,H∞控制综合设计采用包括增量线性化动力学模型、反馈控制器和权阵系数选择的增广对象模型。通过对所设计的先锋无人机的侧向自动着舰导引系统仿真表明,设计能满足着舰要求,并能有效地抑制侧风的影响,具有良好的鲁棒性能。     

Quadrotor Autonomous Approaching and Landing on a Vessel Deck

Autonomous landing of a quadrotor UAV on a vessel deck is challenging due to the special sea environment. In this paper, we present an on-board monocular vision based solution that provides a quadrotor with the capability to autonomously track and land on a vessel deck platform with simulated high sea state conditions. The whole landing process includes two stages: approaching from a long range and landing after hovering above the landing platform. Only on-board sensors are used in both stages, without external information input. We use Parrot AR.Drone as the experimental quadrotor platform, and a self-designed vessel deck emulator is constructed to evaluate the effectiveness of the proposed vessel deck landing solution. Experimental results demonstrate the accuracy and robustness of the developed landing algorithms.     

LANDING AN UNMANNED AIR VEHICLE: VISION BASED MOTION ESTIMATION AND NONLINEAR CONTROL

In this paper, we use computer vision as a feedback sensor in a control loop for landing an unmanned air vehicle (UAV) on a landing pad. The vision problem we address here is then a special case of the classic ego-motion estimation problem since all feature points lie on a planar surface (the landing pad). We study together the discrete and differential versions of the ego-motion estimation, in order to obtain both position and velocity of the UAV relative to the landing pad. After briefly reviewing existing algorithm for the discrete case, we present, in a unified geometric framework, a new estimation scheme for solving the differential case. We further show how the obtained algorithms enable the vision sensor to be placed in the feedback loop as a state observer for landing control. These algorithms are linear, numerically robust, and computationally inexpensive hence suitable for real-time implementation. We present a thorough performance evaluation of the motion estimation algorithms under varying levels of image measurement noise, altitudes of the camera above the landing pad, and different camera motions relative to the landing pad. A landing controller is then designed for a full dynamic model of the UAV. Using geometric nonlinear control theory, the dynamics of the UAV are decoupled into an inner system and outer system. The proposed control scheme is then based on the differential flatness of the outer system. For the overall closed-loop system, conditions are provided under which exponential stability can be guaranteed. In the closed-loop system, the controller is tightly coupled with the vision based state estimation and the only auxiliary sensor are accelerometers for measuring acceleration of the UAV. Finally, we show through simulation results that the designed vision-in-the-loop controller generates stable landing maneuvers even for large levels of image measurement noise. Experiments on a real UAV will be presented in future work.     

Autonomous landing on a moving vehicle with an unmanned aerial vehicle

This paper addresses the perception, control, and trajectory planning for an aerial platform to identify and land on a moving car at 15 km/hr. The hexacopter unmanned aerial vehicle (UAV), equipped with onboard sensors and a computer, detects the car using a monocular camera and predicts the car future movement using a nonlinear motion model. While following the car, the UAV lands on its roof, and it attaches itself using magnetic legs. The proposed system is fully autonomous from takeoff to landing. Numerous field tests were conducted throughout the year‐long development and preparations for the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2017 competition, for which the system was designed. We propose a novel control system in which a model predictive controller is used in real time to generate a reference trajectory for the UAV, which are then tracked by the nonlinear feedback controller. This combination allows to track predictions of the car motion with minimal position error. The evaluation presents three successful autonomous landings during the MBZIRC 2017, where our system achieved the fastest landing among all competing teams.     

Monotonous Trend Estimation of Deck Displacement for Automatic Landing of Rotorcraft UAVs

This paper presents a novel and practical procedure for estimating the mean deck height to assist in automatic landing operations of a Rotorcraft Unmanned Aerial Vehicle (RUAV) in harsh sea environments. A modified Prony Analysis (PA) procedure is outlined to deal with real-time observations of deck displacement, which involves developing an appropriate dynamic model to approach real deck motion with parameters identified through implementing the Forgetting Factor Recursive Least Square (FFRLS) method. The model order is specified using a proper order-selection criterion based on minimizing the summation of accumulated estimation errors. In addition, a feasible threshold criterion is proposed to separate the dominant components of deck displacement, which results in an accurate instantaneous estimation of the mean deck position. Simulation results demonstrate that the proposed recursive procedure exhibits satisfactory estimation performance when applied to real-time deck displacement measurements, making it well suited for integration into ship-RUAV approach and landing guidance systems.     

固定翼无人机自动着陆的一体化制导控制

本文基于制导控制一体化方法的思想,将滑模变结构控制和自抗扰控制技术结合于动态面控制结构中,提出一种固定翼无人机自动着陆方法.在建立六自由度无人机模型、无人机和目标点间的相对视线角度模型的基础上,在动态面控制框架下加入滑模变结构控制来设计制导控制一体化方法.在此过程中加入自抗扰控制技术,提高了系统对未建模部分、参数的不确定性和外界干扰的鲁棒性,并抑制了滑模变结构控制的抖振.该方法使得无人机在平稳地飞向目标点的同时能够满足着陆视线角度的约束.文中详细论述设计思想和设计方法,最后通过仿真验证说明本文方法的有效性.     

无人机的自动着陆控制

无人机的自动着陆控制是无人机控制中的一个难点,文中给出了一种无人机自动着陆的控制方法,并在某型无人机上得到了应用.基于无人机真实的风洞试验数据,利用MATLAB建立了无人机自动着陆的线性化模型和非线性模型,设计了无人机自动着陆导引控制方案及控制律,并在实际飞行试验中得到了验证,最终的飞行试验结果表明了所设计的自动着陆控制律能满足自动着陆的要求,并具有很好的静态和动态特性.     

基于IABC算法的舰载机着舰调度

舰载机有序、高效着舰是确保舰载机舰面保障计划如期进行的必要前提,为提高舰载机着舰效率并减轻传统人工着舰排序的负担,研究一种舰载机着舰调度算法.首先,以加权着舰完成时间和为优化目标,构建舰载机着舰调度的数学模型;其次,提出一种改进的人工蜂群算法用于模型求解,算法在基本人工蜂群算法的基础上引入遗传算法中的交叉算子、精英策略以及一系列自适应局部搜索策略,以增强算法的全局搜索性能,提高算法收敛速度;最后,通过着舰调度案例仿真和算法对比表明,改进的人工蜂群算法具备更强的优化性能和更好的鲁棒性,可以求解大规模舰载机着舰调度问题,具有工程实际应用价值.     

Displacement motion prediction of a landing deck for recovery operations of rotary UAVs

This paper proposes a practical prediction procedure for vertical displacement of a Rotarywing Unmanned Aerial Vehicle (RUAV) landing deck in the presence of stochastic sea state disturbances. A proper time series model tending to capture characteristics of the dynamic relationship between an observer and a landing deck is constructed, with model orders determined by a novel principle based on Bayes Information Criterion (BIC) and coefficients identified using the Forgetting Factor Recursive Least Square (FFRLS) method. In addition, a fast-converging online multi-step predictor is developed, which can be implemented more rapidly than the Auto-Regressive (AR) predictor as it requires less memory allocations when updating coefficients. Simulation results demonstrate that the proposed prediction approach exhibits satisfactory prediction performance, making it suitable for integration into ship-helicopter approach and landing guidance systems in consideration of computational capacity of the flight computer.     

基于卡尔曼滤波理论的甲板运动预估技术研究

航母在航行过程中，海浪运动将会导致舰体产生俯仰、横滚、偏航、上下起伏等运动，这将严重威胁舰载机的着舰安全。为了确保飞机在航母上成功降落，必须在着舰前使飞机运动轨迹与甲板运动同步，因此，本文研究了甲板运动预估技术，运用卡尔曼最优波波理论开发了甲板运动预估器，并提出首先对引入着舰导引系统的甲板运动信息进行预估，然后再进行超前补偿的策略。经仿真验证，甲板运动预估与补偿的结合，可以明显减小舰载机着舰误差，提高着舰精度。     

飞翼布局舰载无人机自主着舰技术研究

舰载无人机自主着舰是舰载机飞行过程中技术复杂、风险最大的环节之一。舰尾流等着舰环境以及甲板的运动是导致着舰产生严重偏差的主要原因。为了掌握环境对着舰过程的影响,需对舰尾流、甲板运动进行建模仿真,尽量真实地反映出理想着舰点的运动情况。在此基础上根据飞翼布局无人机的动力学特性和着舰的技术要求针对飞机纵向着舰设计出理想的下滑轨迹和纵向通道采用高度跟踪控制,横侧向通道采用侧向偏离控制,发动机通道采用基于迎角恒定的动力补偿控制的控制策略。最后结合舰载无人机动力学模型在舰尾流以及甲板运动仿真中实现垂直高度偏差在理想值正负0.78m内、水平位置误差在理想值正负6.1m内的精确着舰,并对方法进行评估验证。     

Robust output tracking control of a laboratory helicopter for automatic landing

In this paper, robust output tracking control problem of a laboratory helicopter for automatic landing in high seas is investigated. The motion of the helicopter is required to synchronise with that of an oscillating platform, e.g. the deck of a vessel subject to wave-induced motions. A robust linear time-invariant output feedback controller consisting of a nominal controller and a robust compensator is designed. The robust compensator is introduced to restrain the influences of parametric uncertainties, nonlinearities and external disturbances. It is shown that robust stability and robust tracking property can be achieved simultaneously. Experimental results on the laboratory helicopter for automatic landing demonstrate the effectiveness of the designed control approach.     

Robust linear output feedback controller for autonomous landing of a quadrotor on a ship deck

Ship deck landing control of a quadrotor requires certain robustness with respect to ship heave motion. Typical systems only provide relative height, therefore do not have relative heave rate information. In this paper, a linear output feedback control consisting of a full state feedback controller and a Luenberger observer is formulated. Invariant ellipsoid method is used to formulate an estimation of a bound on the response of a linear output feedback-controlled system subjected to external disturbances and measurement noise. The gains that result in a minimum bound are optimized using a gradient descent iterative approach proposed in this paper where the invariant ellipsoid condition is linearized into a tractable LMI condition. This approach is applied to a simulation of a quadrotor landing on a ship deck and results are compared with other gains. The gains selected using the proposed approach exhibits improved robustness to external disturbances and measurement noise.     

基于CFD方法的固定翼无人机着陆控制建模

为了实现固定翼无人机低速平稳着陆的目的,以某型无人机为例,阐述以计算流体动力学(CFD)方法求解固定翼无人机气动力系数的过程,即构建飞机几何模型、设定计算域并划分网格、基于非耦合隐式求解器求解在K-E湍流模型下各飞行状态的气动系数.提出以较大迎角低速滑翔降落的着陆控制方法,基于求解的气动特性,计算飞机降落前的理想状态,并基于状态反馈的纵向控制律实现着陆控制.在Simulink环境中,基于AeroSim工具箱构建仿真程序,验证了方法的有效性.     

甲板障碍对舰载机着陆性能影响仿真研究

由于航母在行进中受到海浪起伏影响,舰载机着舰时往往具有较大的相对下沉速度,着陆过程中起落架受到巨大的冲击载荷,严重的情况可能导致飞机失事;为研究着舰过程中飞机起落架动力学特性,基于ADAMS/Aircraft模块,建立某型号舰载机仿真模型,使用三角网格法构建三种典型甲板路面.利用模型进行了舰载机着陆试验仿真,特别研究了舰载机在着陆过程中通过甲板障碍时,飞机起落架载荷的变化情况;研究显示,在机轮触地0.2秒内,起落架载荷达到峰值326722N.而着舰过程中机轮通过甲板障碍时约引起16%的起落架载荷增幅.该增幅的存在将对起落架缓冲性能提出更高的要求,在起落架设计与实验中应充分考虑该因素的影响.     

A Vision-Based Guidance System for UAV Navigation and Safe Landing using Natural Landmarks

In this paper a vision-based approach for guidance and safe landing of an Unmanned Aerial Vehicle (UAV) is proposed. The UAV is required to navigate from an initial to a final position in a partially known environment. The guidance system allows a remote user to define target areas from a high resolution aerial or satellite image to determine either the waypoints of the navigation trajectory or the landing area. A feature-based image-matching algorithm finds the natural landmarks and gives feedbacks to an onboard, hierarchical, behaviour-based control system for autonomous navigation and landing. Two algorithms for safe landing area detection are also proposed, based on a feature optical flow analysis. The main novelty is in the vision-based architecture, extensively tested on a helicopter, which, in particular, does not require any artificial landmark (e.g., helipad). Results show the appropriateness of the vision-based approach, which is robust to occlusions and light variations.     

Automatic Take Off, Tracking and Landing of a Miniature UAV on a Moving Carrier Vehicle

We present a system consisting of a miniature unmanned aerial vehicle (UAV) and a small carrier vehicle, in which the UAV is capable of autonomously starting from the moving ground vehicle, tracking it at a constant distance and landing on a platform on the carrier in motion. Our visual tracking approach differs from other methods by using low-cost, lightweight commodity consumer hardware. As main sensor we use a Wii remote infrared (IR) camera, which allows robust tracking of a pattern of IR lights in conditions without direct sunlight. The system does not need to communicate with the ground vehicle and works with an onboard 8-bit microcontroller. Nevertheless the position and orientation relative to the IR pattern is estimated at a frequency of approximately 50 Hz. This enables the UAV to fly fully autonomously, performing flight control, self-stabilisation and visual tracking of the ground vehicle. We present experiments in which our UAV performs autonomous flights with a moving ground carrier describing a circular path and where the carrier is rotating. The system provides small errors and allows for safe, autonomous indoor flights.     

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.