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第40届中国控制会议

作者： Pengfei Shi Jianglong Yu Ziyan Chen xiwang dong Zhang Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Key Laboratory of Dependable Service Computing in Cyber Physical Society (Chongqing University) Ministry of Education of ChinaChongqing University

This paper studies the finite-time convergent cooperative guidance problem for multiple missiles to achieve the coordination of the flight time. The control variable is relaxed equivalently and an additional term utilizing the local state information is added such that the finite-time convergence being guaranteed. Furthermore, the time-varying coupling gains are introduced in the guidance law and an algorithm to depict the design process is proposed so that the cooperative guidance law for each follower missile is fully distributed. In addition, finite-time convergence of the guidance error is proved based on Lyapunov theory. Finally, a numerical example is displayed to validate the effectiveness of the proposed theoretical results.

关键词： Cooperative guidance finite-time convergence adaptive control

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Distributed Nash equilibrium seeking for non-cooperative convex games with local constraints

Distributed Nash equilibrium seeking for non-cooperative con...

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第40届中国控制会议

作者： Fei Liu Qing Wang Yongzhao Hua xiwang dong Zhang Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control LaboratoryBeihang University Institute of Artificial Intelligence Beihang University

This paper considers the problem of Nash equilibrium seeking in non-cooperative convex games subjected to local constraints including both equality and inequality constraints. Each player in the game is individually associated with a local objective function, which is coupled with the actions of the other players. The players cannot observe the actions of the players that are not their neighbors. Instead, the players are capable of exchanging information of actions via an undirected and connected communication graph. Thus, a leader-following consensus-based estimation of actions of the players is conducted. Furthermore, a Nash equilibrium seeking algorithm is proposed. Stability analysis by means of continuous time Lyapunov approach is presented and it is shown that the algorithm is capable of achieving global convergence to the Nash equilibrium. A numerical example is given to verify the effectiveness of the results of the paper.

关键词： Leader-following consensus Nash equilibrium non-cooperative games local constraints

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Battlefield Situation Deduction and Maneuver Decision Using Deep Q-Learning

Battlefield Situation Deduction and Maneuver Decision Using ...

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第40届中国控制会议

作者： Minghui Shi xiwang dong Liang Han Qingdong Li Zhang Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Key Laboratory of Dependable Service Computing in Cyber Physical Society (Chongqing University) Ministry of Education of ChinaChongqing University School of Sino-French Engineer Beihang University

As the pace and complexity of modern warfare accelerates, it is of great significance to apply intelligent technology to defense decision-making. Due to the high dynamics and randomness of the aircraft, traditional methods are difficult to solve the optimal control strategy. The characteristics of reinforcement learning match the difficulty of the problem. In this paper, the situation of hypersonic aircraft is deduced, and the deep reinforcement learning method is used to make autonomous penetration decisions in the reentry phase. The model of aircraft and environment is established, and the maneuvering decision-making model is established based on deep Q-learning and its optimization algorithm. Through a large number of simulation training,this method can effectively give the real-time decision output of the agent and make a good prediction of the situation. It has the ability of short-range accurate operation and long-term planning and prediction. This method can improve the probability of successful penetration, and can be used as the decision-making basis of glider penetration.

关键词： Hypersonic aircraft situational deduction maneuver decision-making reinforcement learning deep Q-learning

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人与无人机集群多模态智能交互方法

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航空学报 2022年第S1期43卷 129-142页

作者：苏翎菲化永朝董希旺任章北京航空航天大学自动化科学与电气工程学院北京100191 北京航空航天大学人工智能研究院北京100191

针对人与无人机集群交互式协同感知问题,借助深度学习技术,构建了基于语音和手势双模型自主识别集群编队协同控制的交互框架,并提出了一种基于双通道切换的通道融合机制,从而实现多模态交互。使用百度云平台基于流式多级截断注意力(SML... 详细信息

针对人与无人机集群交互式协同感知问题,借助深度学习技术,构建了基于语音和手势双模型自主识别集群编队协同控制的交互框架,并提出了一种基于双通道切换的通道融合机制,从而实现多模态交互。使用百度云平台基于流式多级截断注意力(SMLTA)的语音识别模型,采用深度学习平台进行了自训练,在应用场景下的准确率由80.10%提升至97.98%。结合Kinect V2的深度信息与骨骼信息,构建与训练了基于特征融合的卷积神经网络(CNN)手势识别模型,平均精确率为98.33%,相较于传统决策树模型提升了1.16%,相较于传统CNN模型提升了0.33%。最后,在机器人操作系统(ROS)-Gazebo训练场景下进行了仿真验证和实物验证。实验结果表明:提出的交互框架能有效控制无人机集群进行编队,语音通道、手势通道和通道切换的指令执行成功率均达90%以上,且具有较高的交互效率。

关键词：深度学习人机交互无人机集群语音识别手势识别

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Distributed adaptive finite-time time-varying group formation tracking for high-order multi-agent systems with directed topologies

Distributed adaptive finite-time time-varying group formatio...

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第三十九届中国控制会议

作者： Lei Tian Yongzhao Hua xiwang dong Qingdong Li Zhang Ren School of Automation Science and Electrical Engineering Beihang University Department of Aerospace Engineering University of Bristol Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University

This paper investigates finite-time time-varying group formation（TVGF） tracking control problems for high-order multi-agent systems（MASs） with directed topologies. Firstly, the agents are classified into three types, i.e., the virtual leader, the group leader and the follower. A virtual leader is used to control the macroscopic movement of MASs. Subgroups can be interacted and coordinated with each other by the communication among group leaders. Secondly, a novel finite-time group formation tracking protocol using only the neighboring interaction is constructed based on adaptive integral sliding mode control. Then sufficient conditions for MASs with unknown external disturbances and directed topologies to realize finite-time TVGF tracking are derived using Lyapunov theory. Finally, a numerical simulation example is performed to demonstrate the effectiveness of theoretical results.

关键词： TVGF tracking finite-time control MASs adaptive integral sliding mode control

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Penetration Trajectory Optimization of Hypersonic Gliding Vehicles with Multiple Constraints

Penetration Trajectory Optimization of Hypersonic Gliding Ve...

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第40届中国控制会议

作者： Zhipeng Shen Jianglong Yu xiwang dong Qingdong Li Zhang Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Key Laboratory of Dependable Service Computing in Cyber Physical Society (Chongqing University) Ministry of Education of China Chongqing University

The penetration trajectory optimization problem of hypersonic gliding vehicles（HGV） with multiple constraints is investigated. Firstly, the attack-defense confrontation models are established, where the HGV is required to achieve effective penetration under interception missile using Proportional Navigation Guidance（PNG） method. Then the original penetration trajectory optimization problem under multiple constraints is converted into a second-order cone programming（SOCP） problem through linearization, discretization and convexification manipulation. The online sequential convex optimization algorithm is used to solve the SOCP problem. Finally, numerical simulations are given to demonstrate the effectiveness of the method and penetration effect.

关键词： Penetration Hypersonic gliding vehicles Trajectory optimization Convex optimization Multiple constraints

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NBA-guided heuristic sampling algorithm for multi-robot task planning under temporal logic

NBA-guided heuristic sampling algorithm for multi-robot task...

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第43届中国控制会议

作者： Jiong Luo Yongzhao Hua Shunfu Ding xiwang dong Zhang Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control LaboratoryBeihang University Institute of Artificial Intelligence Beihang University Institute of Unmanned System Beihang University

Aiming at the task planning problem of multi-robot under linear temporal logic(LTL), this paper proposes an improved sampling planning algorithm based on Nondeterministic Büchi automaton(NBA) guidance. Firstly, this paper defines a kind of LTL task planning problem, which mainly focuses on the meaningful key nodes in the task execution of each robot, and there are many sequential dependencies of task constraints. Then, an improved sampling algorithm framework is proposed,which uses a more efficient way to build a search tree and reduces the number of nodes in the tree. Furthermore, the sampling points are guided by NBA to ensure that sampling is conducive to the advancement of time-series tasks. And considering the task feasible region of each robot, the auction algorithm is introduced to optimize the local matching relationship, which greatly improves the quality of sampling points. Finally, numerical simulation is carried out to solve the LTL task planning problem. The optimality and stability of the algorithm are obviously improved, and the time consumption of this algorithm is obviously better than that of the existing advanced algorithms.

关键词： Multi-robot systems sampling-based planning temporal logic task planning NBA-guided

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Deep Reinforcement Learning for Multi-UAVs Collaborative Task Assignment in Logistic Scenarios

Deep Reinforcement Learning for Multi-UAVs Collaborative Tas...

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第43届中国控制会议

作者： Xulin Wang Yongzhao Hua xiwang dong Shuobo Wang Zheng Zhang Institute of Artificial Intelligence Beihang University Institute of Unmanned System Beihang University School of Automation Science and Electrical Engineering Beihang University

This paper proposes a method based on deep reinforcement learning algorithm to solve the collaborative task assignment of multi-UAVs in logistic scenarios. Firstly, the practical logistic scenario is analyzed, a task model based on MDP is established, and the constraints of the logistic assignment problem are given. Secondly, the design and implementation of the state transition function and reward function are implemented based on the established model. This paper averages the final reward into each step to alleviates the problem of reward sparseness in task assignment problem. Then the deep reinforcement learning algorithm Soft Actor-Critic is used to solve the optimization problem. Finally, the experimental results show that the SAC algorithm takes less time to calculate than the traditional algorithm and can have higher average earnings in random environments.

关键词： Deep reinforcement learning Task assignment Multi-UAVs Logistic

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Distributed cooperative guidance for multi-missile system with time-varying delays and switching topologies

Distributed cooperative guidance for multi-missile system wi...

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第三十九届中国控制会议

作者： Siquan Zhou Jie Ren Yong Heng xiwang dong Qingdong Li School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing Aerospace System Engineering Research Institute Beijing Institute of Electronic System Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University

Distributed cooperative guidance problems for multi-missile system with time-varying delays and switching topologies are investigated. Firstly, considering the complex communication environment, a two-step cooperative guidance strategy is proposed to achieve the simultaneous attack under time-varying delays and switching topologies. In the first step, a distributed cooperative guidance law using neighboring information is designed to coordinate range-to-go and leading angle based on feedback linearization and consensus theory. The second step starts while multi missiles disconnect from each other and hit the target using PNG（Proportional Navigation Guidance）. Then, the algorithm with three steps is presented to select the parameters in the cooperative guidance law. And the stability of the multi-missile system is proven using Lyapunov-Krasovskii theory. Finally, a numerical simulation is given to demonstrate the effectiveness of the proposed cooperative guidance strategy.

关键词： Cooperative guidance Distributed strategy Consensus theory Time-varying delays Switching topologies

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Multi-sensor Measurement Information Fusion for Maneuvering Target Recognition and Tracking

Multi-sensor Measurement Information Fusion for Maneuvering ...

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第40届中国控制会议

作者： Zheng Zhang Liang Han xiwang dong Qingdong Li Zhang Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University School of Sino-French Engineer Beihang University Key Laboratory of Dependable Service Computing in Cyber Physical Society (Chongqing University) Ministry of Education of ChinaChongqing University

This paper proposes multi-sensor information fusion algorithm for maneuvering target recognition and tracking based on mobile sensor networks（MSNs）. In order to improve target recognition accuracy, the modified evidence combination rule is designed to obtain the identity information of target based on the Dempster-Shafer（DS） algorithm. The target recognition process is designed by two stages, namely, sensing stage and fusion stage. During the first stage, each sensor node in the MSNs can obtain the feature information of the target, which makes up the measurement information. In the information fusion stage,each sensor combine the information exchanged from neighboring nodes with local measurement information to obtain the highprecise identity information of the maneuvering target based on the improved DS algorithm. Then, the identity information can be used to obtain the accurate state estimation of the maneuvering target. For the purpose of obtaining the accurate state estimation of target, the target tracking process is designed by local filtering stage and fusion stage. Finally, a numerical simulation is designed to illustrate the effectiveness of the algorithm.

关键词： Information Fusion Target Recognition and Tracking Mobile Sensor Network

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