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Multi-UAV cooperative maneuver decision-making for pursuitevasion using improved MADRL

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Defence Technology（防务技术） 2024年第5期35卷 187-197页

作者： delin luo Zihao Fan Ziyi Yang Yang Xu School of Aerospace Engineering Xiamen UniversityXiamen 361102China School of Civil Aviation Northwestern Polytechnical UniversityXi'an 710072China

Aiming at the problem of multi-UAV pursuit-evasion confrontation, a UAV cooperative maneuver method based on an improved multi-agent deep reinforcement learning(MADRL) is proposed. In this method, an improved Comm Net network based on a communication mechanism is introduced into a deep reinforcement learning algorithm to solve the multi-agent problem. A layer of gated recurrent unit(GRU) is added to the actor-network structure to remember historical environmental states. Subsequently,another GRU is designed as a communication channel in the Comm Net core network layer to refine communication information between UAVs. Finally, the simulation results of the algorithm in two sets of scenarios are given, and the results show that the method has good effectiveness and applicability.

关键词： Reinforcement learning UAV Maneuver decision GRU Cooperative control

Segment differential aggregation representation and supervised compensation learning of ConvNets for human action recognition

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Science China(Technological Sciences) 2024年第1期67卷 197-208页

作者： REN ZiLiang ZHANG QieShi CHENG Qin XU ZhenYu YUAN Shuai luo delin School of Computer Science and Technology Dongguan University of TechnologyDongguan 523808China Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhen 518055China School of Electronic Engineering and Automation Guilin University of Electronic TechnologyGuilin 541004China Department of the mechanical engineering Erlangen-Nuremberg UniversityErlangen 91508Germany School of Aerospace Engineering Xiamen UniversityXiamen 361102China

With more multi-modal data available for visual classification tasks,human action recognition has become an increasingly attractive ***,one of the main challenges is to effectively extract complementary features from different modalities for action *** this work,a novel multimodal supervised learning framework based on convolution neural networks(Conv Nets)is proposed to facilitate extracting the compensation features from different modalities for human action *** on information aggregation mechanism and deep Conv Nets,our recognition framework represents spatial-temporal information from the base modalities by a designed frame difference aggregation spatial-temporal module(FDA-STM),that the networks bridges information from skeleton data through a multimodal supervised compensation block(SCB)to supervise the extraction of compensation *** evaluate the proposed recognition framework on three human action datasets,including NTU RGB+D 60,NTU RGB+D 120,and *** results demonstrate that our model with FDA-STM and SCB achieves the state-of-the-art recognition performance on three benchmark datasets.

关键词： action recognition segment frame difference aggregation supervised compensation learning ConvNets

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未知干扰下四旋翼无人机群固定时间编队控制

北京航空航天大学学报 2024年第5期50卷 1702-1712页

作者：郑伟铭徐扬罗德林厦门大学航空航天学院厦门361102 西北工业大学民航学院西安710072 西北工业大学太仓长三角研究院苏州215400

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... 详细信息

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。

关键词：四旋翼无人机欠驱动系统编队控制固定时间控制干扰观测器

基于图卷积深度强化学习的协同空战机动决策方法

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工程科学学报 2024年第7期46卷 1227-1236页

作者：欧洋郭正玉罗德林缪克华厦门大学航空航天学院厦门361102 中国空空导弹研究院洛阳471000 空基信息感知与融合全国重点实验室洛阳471000

针对多无人机智能协同空战对抗决策问题,提出了一种基于长短期记忆与竞争图卷积深度强化学习的多机协同空战机动对抗决策方法.首先,对多机协同空战对抗问题进行描述;其次,在竞争Q网络中,引入长短期记忆网络用于处理带有强时序相关性的... 详细信息

针对多无人机智能协同空战对抗决策问题,提出了一种基于长短期记忆与竞争图卷积深度强化学习的多机协同空战机动对抗决策方法.首先,对多机协同空战对抗问题进行描述;其次,在竞争Q网络中,引入长短期记忆网络用于处理带有强时序相关性的空战信息,接着,搭建图卷积网络作为多机之间的通信基础,提出基于长短期记忆与竞争图卷积深度强化学习算法的协同空战训练框架,并对协同空战决策训练算法进行了设计.二对一空战仿真结果验证了本文所提出的协同智能对抗决策方法的有效性,其具有决策速度快、学习过程稳定的特点以及适应空战环境快速变化下的协同策略学习能力.

关键词：无人机深度强化学习机动决策多机协同空战决策

Multi-UAV cooperative maneuver decision-making for pursuitevasion using improved MADRL

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Dynamic affine formation control of networked under-actuated quad-rotor UAVs with three-dimensional patterns

Defence Technology 2024年第5期 187页

作者： delin luo Zihao Fan Ziyi Yang Yang Xu

来源：博看期刊评论

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Journal of Systems Engineering and Electronics 2022年第6期33卷 1269-1285页

作者： XU Yang ZHENG Weiming luo delin DUAN Haibin School of Civil Aviation Northwestern Polytechnical UniversityXi’an 710072China Yangtze River Delta Research Institute Northwestern Polytechnical UniversityTaicang 215400China School of Aerospace Engineering Xiamen UniversityXiamen 361102China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China

This paper focuses on the solution to the dynamic affine formation control problem for multiple networked underactuated quad-rotor unmanned aerial vehicles(UAVs)to achieve a configuration that preserves collinearity and ratios of distances for a target *** particular,it is investigated that the quad-rotor UAVs are steered to track a reference linear velocity while maintaining a desired three-dimensional target ***,by integrating the properties of the affine transformation and the stress matrix,the design of the target formation is convenient and applicable for various three-dimensional geometric ***,a distributed control method is proposed under a hierarchical *** introducing an intermediary control input for each quad-rotor UAV in the position loop,the necessary thrust input and the desired attitude are *** the attitude loop,the desired attitude represented by the unit quaternion is tracked by the designed torque *** conditions of linear velocity unavailability and mutual collision avoidance are also *** terms of Lyapunov theory,it is prooved that the overall closed-loop error system is asymptotically ***,two illustrative examples are simulated to validate the effectiveness of the proposed theoretical results.

关键词： formation control quad-rotor unmanned aerial vehicle(UAV) hierarchical control

UAV swarm formation reconfiguration control based on variable-stepsize MPC-APCMPIO algorithm

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Science China(Information Sciences) 2023年第11期66卷 222-243页

作者： Jian LIAO Jun CHENG Bin XIN delin luo Lihui ZHENG Yuhang KANG Shaolei ZHOU School of Physics and Electronic Information Gannan Normal University Shenzhen Institute of Advanced Technology Chinese Academy of Sciences School of Automation Beijing Institute of Technology School of Aerospace Engineering Xiamen University School of Electronic Information Northwest University of Technology 6. School of Basic Science Naval Aviation University of PLA

For a complex operational environment, to actualize safe obstacle avoidance and collision avoidance, a swarm must be capable of autonomous formation reconfiguration. First, this paper introduces the basic pigeon-inspired optimization(PIO) algorithm, and establishes the unmanned aerial vehicle motion model and the virtual leader swarm formation control structure. Then, given the above knowledge, the basic error objective function of a UAV swarm, obstacle avoidance objective function, and collision avoidance objective function are devised based on the variable-stepsize model predictive control technique. Next,the adaptive perception Cauchy mutation PIO algorithm is proposed by introducing the Cauchy mutation operator, adaptive weight factor, and roulette wheel selection into the basic PIO. This algorithm is used to optimally solve the abovementioned swarm objective functions. Ultimately, a set of comparative simulations are performed to verify the effectiveness and reliability of the proposed algorithm.

关键词： unmanned aerial vehicle swarm formation reconfiguration variable-stepsize model predictive control (MPC) adaptive perception Cauchy mutation pigeon-inspired optimization (APCMPIO) obstacle avoidance

Distributed planar formation maneuvering of leader-follower networked systems via a barycentric coordinate-based approach

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Science China(Technological Sciences) 2021年第8期64卷 1705-1718页

作者： XU Yang luo delin DUAN HaiBin School of Civil Aviation Northwestern Polytechnical UniversityXi’an710072China School of Aerospace Engineering Xiamen UniversityXiamen361102China School of Automation Science and Electrical Engineering Beihang UniversityBeijing100191China

This paper presents a distributed planar leader-follower formation maneuver control strategy for multi-agent systems with different agent dynamic *** method is based on the barycentric coordinate-based(BCB)control,which can be performed in the local coordinate frame of each agent with required local *** exploring the properties of BCB Laplacians,a time-varying target formation can be BCB localizable by a sufficient number of leaders uniquely,and this formation is converted from a given nominal formation with geometrical similarity *** proposed control laws can continuously maneuver collective single-and double-integrator agents to achieve a translation,scale,rotation,or even their compositions in various *** the formation shape control problem of multi-car systems with/without saturation constraints,the obtained control performance can preserve good *** stability is also proven by mathematical derivations and verified by numerical simulations.

关键词： formation control distributed control multi-agent systems barycentric coordinate

A guidance law for UAV autonomous aerial refueling based on the iterative computation method

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Chinese Journal of Aeronautics 2014年第4期27卷 875-883页

作者： luo delin Xie Rongzeng Duan Haibin Department of Automation Xiamen University State Key Laboratory of Virtual Reality Technology and Systems Beihang University

The rendezvous and formation problem is a significant part for the unmanned aerial vehicle（UAV） autonomous aerial refueling（AAR） technique. It can be divided into two major phases： the long-range guidance phase and the formation phase. In this paper, an iterative computation guidance law（ICGL） is proposed to compute a series of state variables to get the solution of a control variable for a UAV conducting rendezvous with a tanker in AAR. The proposed method can make the control variable converge to zero when the tanker and the UAV receiver come to a formation flight eventually. For the long-range guidance phase, the ICGL divides it into two sub-phases： the correction sub-phase and the guidance sub-phase. The two sub-phases share the same iterative process. As for the formation phase, a velocity coordinate system is created by which control accelerations are designed to make the speed of the UAV consistent with that of the *** simulation results demonstrate that the proposed ICGL is effective and robust against wind disturbance.

关键词： Autonomous aerial refueling Aerial rendezvous Formation control Guidance law Unmanned aerial vehicle