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第43届中国控制会议

作者： Chang Liu Liqian Dou Ruilong Zhang Yifan Tang Mengyuan Ren Lun Zhang School of Electrical Engineering and Automation Beijing Aerospace Automatic Control Institute Tianjin Aerospace Institute of Computing Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Outstanding autonomous evasion decision-making capability has an important significance for ensuring flight safety and enhancing the autonomy of the aircraft. In this paper, a prediction information-based TD3(PITD3) evasion decision-making algorithm for aircraft is proposed, which can autonomously evade the interceptors' attack in an antagonistic environment. Firstly,an antagonistic environment is described according to environmental constraints and the dynamics of the aircraft and interceptor. Secondly, the autonomous decision-making process of the aircraft facing the threat target is modelled as a Markov decision process to describe the state information of the aircraft and interceptor. Finally, an autonomous evasion decision-making method based on the twin delayed deep deterministic policy gradient(TD3) is designed to find the optimal strategy, and the effectiveness of the proposed autonomous evasion decision-making method is demonstrated by simulation results and comparative experiments.

关键词： PITD3 Autonomous Evasion Decision-Making Deep Reinforcement Learning Decision Network Aircraft

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Stability analysis and stabilization of discretized uncertain spatially interconnected systems 27

Stability analysis and stabilization of discretized uncertai...

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27th International Conference on Methods and Models in automation and Robotics, MMAR 2023

作者： Sulikowski, Bartlomiej Galkowski, Krzysztof Hladowski, Lukasz Kummert, Anton Velten, Joerg University of Zielona Góra Institute of Control and Computation Engineering Zielona Góra Poland University of Zielona Góra Institute of Automation Electronic and Electrical Engineering Zielona Góra Poland University of Wuppertal Faculty of Electrical Information and Media Engineering Wuppertal Germany

ISBN: (纸本)9798350311075

In this paper spatially interconnected (ladder) systems have been discussed. First, the multidimensional, in that case, 2D - continuous in time and discrete in the spatial variable, has been introduced. Next, the temporal dynamics has been discretized, which has allowed to create the general, discrete model for the system dynamics. It has been assumed that system elements are the subject of uncertainty of the norm bounded form. Finally, robust stability testing and robust stabilizing controller design conditions have been proposed and its effectiveness is illustrated by an simulation example. © 2023 IEEE.

关键词： Stabilization

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Mean policy-based proximal policy optimization for maneuvering decision in multi-UAV air combat

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Neural Computing and Applications 2024年第31期36卷 19667-19690页

作者： Zheng, Yifan Xin, Bin He, Bin Ding, Yulong Department of Control Science and Engineering Tongji University Shanghai China Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai China School of Automation Beijing Institute of Technology Beijing China National Key Lab of Autonomous Intelligent Unmanned Systems Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

Autonomous maneuvering decision-making is a crucial technology for Unmanned Aerial Vehicles (UAVs) to take the air domination in modern unmanned warfare. With the advantage of balancing exploration and exploitation, as well as the immediacy of end-to-end output by combining with deep neural network, multi-agent reinforcement learning (MARL) has made remarkable achievements in multi-UAV autonomous air combat maneuvering decision-making (MUAAMD). However, the implementation of effective cooperative policy learning remains a challenging issue for MARL methods with centralized training decentralized execution (CTDE) paradigm. This paper proposes a MARL-based method to improve the performance of cooperation in MUAAMD. Firstly, considering the constraints of dynamic and limited perception for UAVs in the realistic air combat scenario, the MUAAMD problem is formulated based on partially observable Markov game (POMG) model. Secondly, a novel efficient MARL algorithm named the mean policy-based proximal policy optimization (MP3O) is introduced. Specifically, a joint policy optimization mechanism is constructed by estimating the policies of neighboring agents in group as a mean-field approximation while training, which enables both centralized evaluation and improvement of cooperative policy under the CTDE paradigm. Thirdly, by combining with three improvement techniques, a cooperative decision-making framework for MUAAMD based on MP3O is proposed. Empirically, results of simulations and comparative experiments validate the effectiveness of proposed method in promoting cooperative policy learning in resolving MUAAMD problem. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Decision making

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A proposed Power Converter for an AC Battery

A proposed Power Converter for an AC Battery

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International Conference on Communications and Electronics, ICCE

作者： Tuan Anh Do Phu Quang Nguyen Tien Dat Vu Trung Nghia Le Vuong Anh Le Ta Truong Linh Luu Xuan Tung Bui Duy Phuoc Pham Ba Manh Nguyen Quang Dich Nguyen Viet Phuong Pham Phuong Vu Hoang Hanoi University of Science and Technology Hanoi Vietnam Institute for Control Engineering and Automation Hanoi Vietnam

ISBN: (数字)9798350379792

ISBN: (纸本)9798350379808

The paper proposes a novel structure of an AC Battery with a two-stage topology. The Three-port converter (TPC) is proposed for the DC/DC stage to connect with multiple voltage standards of the second-lifetime batteries. The Four-Leg converter is proposed for the DC/AC stage to flexibly operate both with the single-phase and three-phase grid or load. Additionally, a control structure for the proposed AC Battery is presented. Finally, the operating principle of a three-phase AC Battery is validated through Matlab/Simulink simulations. The simulation results show the effectiveness and feasibility of the proposed AC Battery

关键词： Simulation Batteries Topology Standards Matlab Load modeling

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Cutting force and specific energy for rotary ultrasonic drilling based on kinematics analysis of vibration effectiveness

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Chinese Journal of Aeronautics 2022年第1期35卷 376-387页

作者： Zhen LI Songmei YUAN Jiang MA Jun SHEN Andre D.L.BATAKO College of Mechatronics and Control Engineering.Shenzhen University Shenzhen 518060China College of Physics and Optoelectronic Engineering Shenzhen UniversityShenzhen 518060China School of Mechanical Engineering and Automation Beihang UniversityBeijing 100083China The General Engineering&Techmology Research Institute Liverpool John Moores UniversitLiverpool L33AF.UK

Rotary ultrasonic drilling(RUD)has become an effective approach for machining advanced composites which are widely using in the field of *** cutting kinematics and the corresponding material removal mechanisms are distinct in different drilling areas during ***,these fundamentals have not been fully considered in the existing *** this research,two distinct forms of interaction induced by ultrasonic vibration were considered as impact-separation and vibratory lapping between the abrasives and *** the conditions to guarantee the effectiveness of these interactions were obtained to eliminate diminishing effects of ultrasonic *** on indentation fracture theory,the penetration depth of abrasives and the axial drilling force model was derived for *** verification tests of C/SiC composites resulted in a prediction error within 15%.Due to the minimal volume of material removed during each vibration cycle,the drilling force was more stable in vibration assisted *** specific drilling energy of RUD was firstly calculated based on the measured drilling *** was found the drilling parameters should be matched with vibration frequency and amplitude to make better usage of the advantages of ultrasonic vibration,which is critical in the vibration assisted processing of advanced materials.

关键词： Ceramic matrix composite Drilling force modelling Kinematics analysis Rotary ultrasonic drilling Specific drilling energy Vibration diminishing effect

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MA-RRT∗ Algorithm for Path Planning with Maximum Rotation Angle Constraint and Adaptive Crossing Threat Zone 42

MA-RRT∗ Algorithm for Path Planning with Maximum Rotation A...

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42nd Chinese control Conference, CCC 2023

作者： Luo, Jiong Heng, Yong Li, Qi Hua, Yongzhao Dong, Xiwang Ren, Zhang School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Beijing Institute of Electronic System Engineering Beijing100854 China Institute of Artificial Intelligence Beihang University Beijing100191 China

ISBN: (纸本)9789887581543

With the gradual diversification of modern application scenes, the demand for UAV path planning is becoming more and more abundant. This paper first introduces a possible battle scenario, and the problems that must be considered in path planning in this scene are analyzed: the maximum rotation angle constraint and the demand that the UAV can cross the threat zone flexibly. Maximum rotation angle and Adaptive crossing threat zone RRT∗(MA-RRT∗) algorithm is proposed to solve the above problems. The algorithm improves the reconnection process of neighbor set in RRT∗, and adds the maximum rotation angle constraint to the RRT∗ framework, so that the generated path strictly meets this constraint. In addition, the above process also reduces the time consumption of RRT∗, and the speed advantage of MA-RRT∗ becomes more and more obvious with the increase of iteration times. Then, the obstacle information is regarded as one of the components of the node cost of the path, and the original obstacle is regarded as a soft constraint. This enables the path to adaptively cross the threat zone, which is more in line with the actual situation. We compare our algorithm with RRT∗ in numerical simulation, which verifies the effectiveness and time consumption advantages of the algorithm. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Motion planning

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Fixed-Time Sliding Mode control of QUAV Attitude System Based on Disturbance Observer

Fixed-Time Sliding Mode Control of QUAV Attitude System Base...

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Chinese automation Congress (CAC)

作者： Yunjie Gao Yingjiang Zhou Guoping Jiang Ming Lu Zhihao Fan School of Automation and Artificial Intelligence Nanjing University of Posts and Telecommunications Beijing Institute of Control Engineering

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

In this paper, the fixed-time stability of the attitude system of a quadrotor unmanned aerial vehicle (QUAV) under external time-varying disturbance is investigated. A novel disturbance observer with state dependent variables as exponents is designed to estimate time-varying perturbations. Subsequently, a fixed - time controller is engineered to achieve fixed-time convergence of the QUAV's attitude system. The efficacy of the proposed algorithm is validated through numerical simulation.

关键词： Attitude control Perturbation methods Numerical simulation Disturbance observers Stability analysis Time-varying systems Sliding mode control Numerical stability Convergence Quadrotors

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Fault diagnosis of control moment gyroscope based on a new CNN scheme using attention-enhanced convolutional block

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Science China(Technological Sciences) 2022年第11期65卷 2605-2616页

作者： ZHAO HaoTian LIU Ming SUN YiYong CHEN Zhang DUAN GuangRen CAO XiBin Research Center of Satellite Technology School of AstronauticsHarbin Institute of TechnologyHarbin 150001China School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China Department of Automation TsinghuaUniversityBeijing 100084China Control Theory and Guidance Technology School of AstronauticsHarbin Institute of TechnologyHarbin150001China

control moment gyroscope(CMG)is a typical attitude control system component for satellites and mobile robots,and the online fault diagnosis of CMG is crucial because it determines the stability and accuracy of the attitude control *** paper develops a data-driven CMG fault diagnosis scheme based on a new CNN *** this design,seven types of fault signals are converted into spectrum datasets through short-time Fourier transformation(STFT),and a new CNN network scheme called AECB-CNN is proposed based on attention-enhanced convolutional blocks(AECB).AECB-CNN can achieve high training accuracy for the CMG fault diagnosis datasets under different sliding window ***,simulation results indicate that the proposed fault diagnosis method can achieve an accuracy of nearly 95%in 1.28 s and 100%in 2.56 s,respectively.

关键词： fault diagnosis control moment gyroscope CNN scheme attention-enhanced convolutional block

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Distributed Secure Surrounding control for Multiple USVs against Deception Attacks: A Stackelberg Game Approach with Reinforcement Learning

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-12页

作者： Wang, Qiang Liu, Chun Lan, Jianglin Ren, Xiaoqiang Meng, Yizhen Wang, Xiaofan School of Mechatronic Engineering and Automation Shanghai University Shanghai China School of Mechatronic Engineering and Automation James Watt School of Engineering University of Glasgow Glasgow U.K Shanghai Aerospace Control Technology Institute

This article investigates the Stackelberg game-based distributed secure surrounding control (SSC) problem for multiple unmanned surface vehicles (USVs) with unknown dynamics under deception attacks (DAs). The proposed scheme is rooted in the Stackelberg game with reinforcement learning (RL), in which the attacker and controller respectively play the roles of the follower and leader, making sequential decisions of the DA and the SSC. Specifically, a distributed target estimator is established to access the target position. By utilizing this estimated position to formulate an intermediate control law, the target surrounding scenario is effectively transformed into the Stackelberg game-solving problem. The RL approach with a neural networks-based actor-critic learning structure is deployed to directly derive the distributed optimal SSC and DA policies from the Bellman error, whilst learning the unknown dynamics of USVs. Moreover, a value function decomposition technique is applied optimally for using the designed control parameters, thereby accelerating the acquisition of optimal policies. A rigorous theoretical analysis is employed to ensure the closed-loop stability of multiple USVs. Simulations are provided to validate the effectiveness of the proposed distributed SSC scheme for multiple USVs. IEEE

关键词： Reinforcement learning

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A High-Precision Edge Detection Algorithm Based on Improved Sobel Operator-Assisted HED 14

A High-Precision Edge Detection Algorithm Based on Improved ...

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14th IEEE International Conference on Cyber Technology in automation, control, and Intelligent Systems, CYBER 2024

作者： Yuan, Yeborui Chen, Wenyuan Tang, Jie Yang, Jia School of Electrical Engineering and Automation Tianjin University of Technology Tianjin300384 China Shenyang Institute of Automation Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang State Key Laboratory of Robotics 110016 China University of Chinese Academy of Sciences Beijing100049 China School of Electrical Engineering and Automation Tianjin University of Technology Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Tianjin300384 China

ISBN: (纸本)9798331506056

In response to the problem of poor detection performance of the traditional Sobel operator in edge detection, a high-precision edge detection algorithm based on Sobel operator-assisted Holistically-nested Edge Detection (HED) network was proposed, which is named ISAHED here. The algorithm is designed as follows. Firstly, an improved Sobel operator based on the traditional Sobel operator was proposed through adding gradient direction. Then, the image output by the improved Sobel operator is taken as the ground-truth image and as the end-to-end comparison object in a HED-like network. Finally, the ISAHED algorithm outputs edge images with better quality through iterative learning of the HED-like neural network. The experimental results prove that the proposed ISAHED algorithm has better edge detection performance by visually observing the final edge images and further evaluating the values of FOM. This work provides an important reference for the further development of the edge detection technology. © 2024 IEEE.

关键词： Contrastive Learning

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