Modeling, Analysis, Numerical Simulation of the Delayed Stochastic Systems with Applications
邓飞其 教授
华南理工大学，中国
摘要
The understanding of the talker about the stochastic phenomenon and the stochastic system models, as well as the recent progresses achieved by his group about the research on the theory of the delayed stochastic systems, will be introduced, including: 1. Those on the fundamental theories, e.g. the nonnegative semi-martingale boundedness lemma, the improvement on the Doob’s martingale inequality, the implication theorem for the stability of the delayed stochastic systems; 2. Some interesting discoveries on the control theory of the delayed stochastic systems, e.g. the reachability the states of the delayed stochastic systems to zeros, the stabilizability of some uncontrollable systems by delayed feedbacks, the stabilization of the stochastic systems by feedbacks with unbounded or over large time delays; 3. Some progresses on the control theory of the delayed stochastic systems, e.g. the divided feedback stabilization of the stochastic systems, the accurate numerical schemes of the stochastic systems with sampled data with applications, the stability of the networked control systems. Besidess, some challenges will be presented, e.g. the event-triggering control of the stochastic systems, the boundedness of the solutions of the stochastic systems by deterministic bounds, etc. Communications on related topics with the participants are expected.
个人简介
邓飞其，1983年毕业于湖南大学应用数学专业，获学士学位，1997年毕业于华南理工大学自动控制专业，获工学博士学位。历任华南理工大学工业技术研究总院院长、中国民主同盟中央委员会委员、广东省委副主委、广东省政常委，广东省人民政府参事、华南理工大学学术委员会委员、中国仿真学会不确定性系统分析与仿真专业委员会副主任委员等职，现为华南理工大学系统工程研究所所长、IFAC Technical Committee on Stochastic Systems主席、IEEE Technical Committee on the Cybernetics of the Complex Systems主席、IEEE CSS Guangzhou Chapter主席、中国自动化学会会士、中国自动化学会控制理论专业委员会（TCCT）委员、关肇直奖评奖委员会委员、广东省物联网技术标准委员会主任、TCCT随机系统控制学组主任，中国仿真学会不确定性系统分析与仿真专业委员会委员；主要研究复杂系统控制理论与智能技术，主持国家基金重点项目，出版专著4部，发表论文600多篇；获得2002年度国务院特殊津贴，获得第七届丁颖科技奖；获得教育部自然科学二等奖，广东省自然科学二等奖；连续入选全球前2%顶尖科学家、全球高排名学者榜单；2016、2021、2025年度中国自动化学会优秀博士论文奖指导教师。
UAV Swarm Inspired by Bird Flock Intelligence Incentive and Convergence
段海滨 教授
北京航空航天大学，中国
摘要
Nature is a rich source of human creativity. On the basis of a series of flight experiments on bird flock behavior in nature, the internal mechanism of different behavior phenomena of birds is analyzed through collecting and processing the experimental data of different flight behavior of birds, and the bird flock intelligence incentive and convergence behaviors are modeled. The positive and negative feedback mechanism model of bird flock intelligence emergence is constructed. The mapping relationship between the bird flock intelligence incentive and convergence and the flight of unmanned aerial vehicles (UAVs) is studied. Inspired by the different behavior models of bird flock intelligence incentive and convergence, the UAV cooperative searching method based on the bird flock intelligence incentive and the UAV swarm countermeasure method based on the bird flock intelligence convergence are proposed. The recent progresses in incentive and convergence in bird flock intelligence will also be highlighted.
个人简介
段海滨，中国自动化学会会士、中国人工智能学会会士。国家杰出青年科学基金获得者，教育部长江学者特聘教授，“万人计划”-科技创新领军人才、首批青年拔尖人才。主要从事无人机集群仿生自主飞行控制及应用研究。
主持国家自然基金重大研究计划重点项目、国家自然科学基金原创探索计划重点项目、国家自然科学基金叶企孙科学基金、国家自然科学基金企业创新联合基金重点项目、国家自然科学基金重点项目、国家杰出青年科学基金、军委科技委创新特区项目、装备预研等课题。发表SCI论文90余篇，专著4部，发明专利51项，2020-2025年爱思唯尔中国高被引学者，获吴文俊人工智能自然科学一等奖、CAA自然科学一等奖、CAA技术发明一等奖、中国航空学会科学技术一等奖、吴文俊人工智能科技创新一等奖、国防技术发明二等奖、国防科技进步二等奖、北京市科学技术奖自然科学二等奖(均排名1)，高等教育国家级教学成果二等奖(排名2)、高等教育国家级教学成果一等奖(排名5)。获中国青年科技奖、全国优秀科技工作者、中国青年五四奖章、茅以升北京青年科技奖、中国自动化学会首届青年科学家奖、杨家墀科技奖、冯如航空科技精英奖。《Guidance, Navigation and Control》创刊主编(入选2022中国科技期刊卓越行动计划高起点新刊，E-SCI期刊)，《自动化学报》和《工程科学学报》副主编，《IEEE Trans Cybernetics》、《IEEE Transactions on Circuits and Systems I: Regular Papers》、《IEEE Transactions on Circuits and Systems II: Express Briefs》、《中国科学：信息科学(中、英文版)》、《中国科学：技术科学(中、英文版)》、《智能系统学报》等编委，IFAC TC(自主智能系统委员会) 7.5委员、中国自动化学会无人飞行器自主控制专业委员会主任、中国航空学会制导导航与控制分会主任。
Applications of the Fully Actuated System Theory on the Nonlinear Control of Robots and UAVs
刘万泉 教授
中山大学，中国
摘要
In this seminar, I will establish some novel strategies for robot control within the recently proposed fully actuated system framework. Some critical challenges, including predefined-time consensus, input constraints, nonholonomic constraints, and heterogeneous cooperation, are systematically addressed. Firstly, for omnidirectional mobile robots operating in complex environments, a predefined-time consensus control scheme is developed under input constraints, nonholonomic constraints, and collision-free formation requirements. A novel fully actuated predefined-time behavioural control strategy is developed by integrating a predefined-time cooperative protocol with a null-space-based behavioural control mechanism, thereby enabling distributed formation control. Secondly, for tendon-driven manipulators, a fully actuated control framework based on model predictive control (MPC) is established to address input constraints, strong coupling, and vibration induced by high-frequency torque variations. In both cases, by exploiting the fully actuated transformation, complex nonlinear dynamics are reformulated into a tractable linear form, significantly reducing controller design complexity. Finally, for heterogeneous air–ground cooperative systems, a unified fully actuated modelling and control approach is developed to address dynamic discrepancies among heterogeneous robots and to reduce reliance on accurate nonlinear models. By transforming the dynamics of unmanned aerial vehicles and ground vehicles into a unified, fully actuated representation, distributed consensus-based formation control can be achieved, resulting in better coordination accuracy and system stability. In summary, a unified fully actuated system control framework is established for some typical robot control problems, to systematically address critical issues brought by the nonlinear complexity.
个人简介
刘万泉博士： 中山大学智能工程学院教授，国家特聘专家。1985年获曲阜师范大学数学学士学位，1988年获中科院系统科学研究所运筹学与控制论硕士学位，1993年获上海交通大学博士学位。1993年至2021年在澳大利亚西澳大学，悉尼大学和科挺大学工作28年。曾获悉尼大学U2000研究员，澳大利亚基金委杰出研究员（ARC Fellow）和日本JSPS高级研究员多项科研人才称号。2015年获北京市海聚人才计划，2018年获镇江市2025智能制造领军人才。 2021年获中山大学百人计划领军人才， 同年获深圳市孔雀人才计划。 2022年获广东省珠江领军人才与国家特聘专家。 他在国际知名杂志与重要会议发表论450多篇。担任国际杂志Mathematical Foundation of Computing 的主编与多个国际杂志的编委。 他目前的研究方向是机器学习，智能控制与智慧养老与康复。
From Artificial Intelligence to Embodied Intelligence
刘勇 教授
浙江大学控制科学与工程学院，中国
摘要
Embodied intelligence has promising application potential across various fields, including industrial manufacturing, autonomous driving, logistics and transportation, household services, medical care and elderly health, among others. This report will briefly review the historical evolution from the boom of artificial intelligence to the emergence of embodied intelligence, and outline its core components and implementation approaches.
个人简介
刘勇，浙江大学控制科学与工程学院教授，浙江大学控制学院智能驾驶与未来交通中心主任，浙江大学-天数智芯先进智能计算联合研发中心主任，浙江大学先进智能系统研究中心副主任，浙江大学控制科学与工程学院党委委员，浙江省机器换人专家。承担国家自然科学青年科学基金项目（A类），获中国专利银奖、浙江省自然科学一等奖、浙江省科学技术一等奖、浙江省科学技术进步一等奖、浙江省知识产权专利奖一等奖、浙江省自然科学学术二等奖、浙江省杰出青年科学基金项目，入选中组部万人计划青年拔尖人才、浙江省有突出贡献青年科技人才、2022年杭州市钱江特聘专家和浙江省 151 人才项目，以第一作者或通讯作者在TPAMI、TRO、IJCV、JMLR、TIP、CVPR、ICCV、ECCV、NeurIPS、ICLR、ICRA、IROS等知名期刊和机器人/计算机视觉顶级会议发表论文百余篇。主要研究方向为：自主机器人与智能系统、机器人自主规划与导航控制、视觉识别与模式识别、SLAM技术及多传感器融合技术。
From Model-Free Self-Learning Control to Multi-Agent Decision Optimization
王友清 教授
北京化工大学，中国
摘要
In the control and optimization of complex systems, model-free characteristics, uncertainties, and external disturbances are ubiquitous, posing significant challenges to traditional optimal control methods that rely on accurate system models. In recent years, researchers have explored theories and methods of self-learning and optimization from various perspectives. On the one hand, efforts focus on model-free optimal control at the control level to achieve efficient system operation; on the other hand, they extend to game-theoretic optimization at the decision level to characterize competitive and cooperative behaviors in complex environments.
At the control level, we systematically investigate an adaptive dynamic programming (ADP) approach based on the internal model principle to address the output regulation problem for both linear discrete-time and continuous-time systems. By introducing an improved algorithm based on state reconstruction, we overcome the limitation of unknown exosystem parameters, significantly enhancing robustness and practical applicability. This framework is further applied to power electronic systems, enabling independent regulation of active and reactive power in virtual synchronous generators (VSGs) and ensuring safe operation of Buck converters.
At the decision level, we investigate line-of-sight pursuit-evasion games, a class of adversarial optimization problems with geometric constraints. For line-of-sight pursuit-evasion games in environments with multiple obstacles, we construct state value functions based on geometric modeling and derive optimal strategies via Nash equilibrium. Furthermore, by integrating geometric modeling with differential game theory, we solve for optimal strategies in corner-obstacle scenarios with attack range, thereby enhancing the decision-making capability of agents in complex environments.
个人简介
王友清，国家杰出青年基金获得者、IET Fellow、中国自动化学会会士，北京化工大学教授/博导，信息科学与技术学院院长。王友清担任9个SCI期刊的编委或客座编委，还是3个IFAC技术委员会的委员。他荣获教育部、北京市、山东省自然科学奖各一项。出版专著3本，以第一或通讯作者发表SCI论文160余篇。获得20余项发明专利授权，研究成果在中石化、中石油等头部企业得到应用。论文被SCI引用6000多次。引用者包括40余位国内外院士，16篇论文曾入选ESI热点论文或高被引论文，施引单位遍布80多个国家。他多次入选《年度全球前2％顶尖科学家榜单》的“终身科学影响力排行榜”和“年度科学影响力排行榜”。
Analysis and Control of Stochastic Nonlinear Systems
徐胜元 教授
南京理工大学，中国
摘要
This talk focuses on the multi-faceted, coupled challenges including stochastic disturbances, inherent nonlinearities, and signal time delays encountered by complex equipment such as high-precision fire control systems. Centering on three core frontier issues in the control of stochastic nonlinear systems--the complete elimination of nonlinear growth conditions, the effective reduction of controller complexity, and the transformative enhancement of system dynamic performance, the talk systematically elucidates the latest theoretical breakthroughs in this field. It establishes a comprehensive stability theory framework designed to guarantee the rapid and precise convergence of such systems, aiming to provide the theoretical framework and methodological support necessary for the construction of high-performance stochastic control systems.
个人简介
徐胜元, 国家杰出青年科学基金获得者，教育部长江学者特聘教授，教育部创新团队学术带头人，基金委创新研究群体项目负责人，2019年度国家自然科学二等奖获得者。
1990年于杭州师范学院获理学学士学位，1996年于曲阜师范大学获理学硕士学位，1999年于南京理工大学获工学博士学位。2000年12月至2001年11月在比利时鲁汶大学做博士后研究，2001年12月至2002年9月在加拿大艾尔伯特大学做博士后研究，2002年9月至2003年9月获聘为香港大学William Mong青年研究员。现为南京理工大学自动化学院教授，博士生导师。
Theoretical Research and Practice with Intelligent Control and Fully Actuated System for Wind Turbines
杨秦敏 教授
浙江大学，中国
摘要
Wind energy has been considered to be a promising alternative to current fossil-based energies. Large-scale wind turbines have been widely deployed to substantiate the renewable energy strategy of various countries. In this talk, challenges faced by control community for high reliable and efficient exploitation of wind energy are discussed. Advanced controllers including intelligent control and fully actuated system are designed to (partially) overcome problems, such as uncertainty, intermittence, and intense dynamics. Theoretical results and attempts for practice are both present.
个人简介
杨秦敏，浙江大学求是特聘教授，入选教育部长江学者。在美国密苏里大学获电子工程博士学位，曾任Caterpillar公司高级系统工程师。先后主持自然科学基金联合重点、面上项目、科技部863课题、工信部智能制造课题等项目。现为IEEE高级会员，中国自动化学会ADPRL专委会副主任，控制理论专委会新能源学组秘书长，担任IEEE TNNLS，TSMC: Systems，TASE, TMECH，TIMC等国内外期刊编委。曾获浙江省科技进步一等奖、二等奖、自动化学会科技进步一等奖、自动化学会优博论文导师奖、浙江省万人计划领军人才等荣誉。
Fundamental problems of finite-information systems
张纪峰 研究员
中原工学院/中科院数学院，中国
摘要
In networked systems, how to reduce the cost of data measurement and transmission for each node, and how to eliminate the adverse effects that uncertainties in measurement and transmission bring to closed-loop system performance, is a fundamental problem that control theory urgently needs to solve, and is also an extremely challenging issue. Theoretically, this requires addressing the question of 'how much information is needed to accomplish a given control task, and methodologically, it requires solving the integrated design problem of communication and control in multi-agent systems. This report will introduce some of the results our research group has achieved in recent years in this area, including parameter identification and control based on quantized and aggregated data, integrated design methods for communication and control in multi-agent systems, and convergence control design and closed-loop system performance analysis based on low-capacity channels.
个人简介
张纪峰，中原工学院学术副校长、中国科学院数学与系统科学研究院研究员。研究方向为随机系统、有限信息系统、多自主体系统的分析与控制等。曾两次获国家自然科学二等奖，现为IEEE Fellow、IFAC Fellow、欧洲科学与艺术院院士、中国自动化学会会士、中国工业与应用数学学会会士。先后任中国科学院数学与系统科学研究院系统所所长，国务院学位委员会系统科学评议组召集人，国际自动控制联合会技术局副主席，中国自动化学会、中国数学会和中国系统工程学会等的副理事长，十多个国内外重要学术期刊的主编、副主编或编委，是科普期刊《系统与控制纵横》的创刊主编。先后主持国家杰出青年基金项目、重点项目，以及科技部重点研发项目、973课题等。
Intelligent sensing, intelligent control, intelligent scheduling, and AI security
张颖伟 教授
东北大学，中国
摘要
The new generation of artificial intelligence" achieves virtual-real twin evolution and inverse reasoning in manufacturing operations based on the industrial internet, innovating intelligent perception approaches for comprehensive integration of full-factor data in complex manufacturing systems. It provides methods to address intelligent control and scheduling challenges in open industrial internet environments, breaks through large-scale intelligent technology bottlenecks for cost reduction and efficiency improvement, and tackles group intelligent optimization decision-making technologies. From both theoretical and practical perspectives, it facilitates exchanges and discussions on the research status, progress, achievements (theoretical and experimental), and existing challenging issues of industrial internet and "new generation artificial intelligence" related technologies in intelligent perception, intelligent control, intelligent scheduling, and AI security.
个人简介
Zhang Yingwei, Professor and Doctoral Supervisor at Northeastern University. Obtained double bachelor's degrees from Harbin Institute of Technology and master's and doctoral degrees in Control Theory and Control Engineering from Northeastern University. Recipient of the National Outstanding Youth Science Fund, Changjiang Scholar Distinguished Professor of the Ministry of Education, recipient of the State Council Government Special Allowance, national level candidate for the Hundred, Thousand, and Ten Thousand Talents Project, Chief of the Science and Technology Innovation 2030- "New Generation Artificial Intelligence" Major Project, member of the Provincial Science and Technology Innovation Team, and member of the Provincial Political Consultative Conference. My research focuses on industrial intelligence technologies such as complex working condition recognition, autonomous digital twin, physical artificial intelligence, industrial big data and image science, process monitoring and quality prediction, machine learning and deep learning, multi-agent and evolutionary game theory, intelligent planning and resource scheduling, as well as engineering applications in steel manufacturing, large aircraft manufacturing, equipment chip manufacturing, energy industry, and rocket military industry.
面向复杂环境的仿海胆机器人机动技术
赵旭东 教授
大连理工大学，中国
摘要
针对抢滩登陆中浅滩、礁石等复杂地形环境下隐蔽侦察任务的机动需求，发挥仿生类无人系统高隐蔽性和“不怕伤亡”天然优势，及可快速部署并进入到有人作战力量无法或不便涉足的危险、恶劣环境和空间中等特点。开展自适应类海胆仿生机器人总体技术研究和基于深度学习和自主学习的控制研究，研制原理样机并开展实验验证。本报告将介绍仿海胆机器人研发的几个研究结果，主要包括：设计灵感及硬件结构设计、基于动力学的运动控制、基于强化学习的运动控制、 仿真及样机实验。
个人简介
赵旭东，大连理工大学教授，博士生导师， “工业装备智能控制与优化教育部重点实验室”副主任。入选国家级领军人才支持计划。近年来在切换系统、不确定系统、几类非线性系统的稳定性、鲁棒控制、智能控制及其在航空发动机、机器人的应用等领域取得了一系列的研究成果。在Automatica及IEEE Transactions系列汇刊发表论文160余篇，其中包括控制领域顶级期刊Automatica和IEEE TAC 20余篇。 科研成果被引用20000余次，多篇学术论文入选ESI-TOP高被引论文。主持国家科技重大专项（首席科学家），国家重点研发计划项目，国家自然科学基金重点项目，国家优青项目，JKW某工程项目，两机重大专项课题等多个重要项目。获得全球高被引科学家奖（Web of Science）、USERN青年科学家奖、中国自动化学会青年科学家奖；获得教育部自然科学二等奖、中国自动化学会自然科学一等奖等科技奖励8项；出版英文专著2部；授权国家发明专利10余项。担任中国指挥与控制学会智能控制与系统专业委员会常务委员、集群智能与协同控制专业委员会常务委员，中国空天动力联合会发动机控制技术专业委员会委员，中国机械学会机器人专业委员会委员。担任《自动化学报》、《控制工程》及SCI期刊《IEEE Transactions on Systems, Man and Cybernetics: Systems》、《Nonlinear Analysis: Hybrid Systems》等编委工作,同时担任《Engineering Reports》顾问委员会委员。
Robust Optimal Adaptive Control for Fully Actuated Uncertain Nonlinear Systems with Applications
顾国祥 教授
Louisiana State University
摘要
We investigate adaptive control for a class of fully actuated uncertain nonlinear systems under state feedback. It is shown that adaptive control of such a class of nonlinear systems is hinged on the linear part. New results include:
• Global asymptotic stabilization (GAS).
• Input-to-state stability (ISS) and exponential stability (ES).
• Output regulation (OR) with full information (FI) and LQR control.
• Robust control and disturbance rejection under H∞-framework.
• Applications to platoon control in achieving disturbance string stability (DSS).
The results are illustrated by simulation studies.
个人简介
Guoxiang Gu (F’10) received the Ph.D. degree in Electrical Engineering from University of Minnesota, Minneapolis, MN, USA, in 1988. From 1988 to 1990, he was with the Department of Electrical Engineering, Wright State University, Dayton, OH, USA, as a Visiting Assistant Professor. He has held visiting positions with Wright-Patterson Air Force Base, OH, USA, and with the Hong Kong University of Science and Technology, Hong Kong. He worked for Louisiana State University (LSU), Baton Rouge, LA, USA, and was a Professor of Electrical and Computer Engineering and F. Hugh Coughlin/CLECO Distinguished Professor of LSU. He has authored two books, over 90 archive journal papers, and numerous book chapters and conference papers. His research interests include networked control systems, modeling and identification, and industrial applications. Dr. Gu served as an Associate Editor for IEEE Transactions on Automatic Control from January 1998 to December 2001 and from January 2018 to December 2021, SIAM Journal on Control and Optimization from 2006 to 2009, and Automatica from 2006 to 2012. He is currently a Professor of Xinan Jiaotong University, an Emeritus Professor in ECE of LSU and Fellow of IEEE.
Deep learning methodology development for multimodal molecular data analysis
沈红斌 教授
上海交通大学，中国
摘要
With the rapidly increasing protein and related molecular data, understanding the hidden knowledge behind the data, and revealing the hidden relationship between different sources of data is one of the promising interdisciplinary research directions of computer science and life sciences. Multimodal information of molecular sequence, structure and other modal data complement each other. Developing efficient multimodal pattern embedding and data-driven deep learning and pattern recognition algorithms is helpful for speeding up the understanding of molecular big data.
个人简介
上海交通大学特聘教授，曾获国家杰出青年科学基金、万人计划青年拔尖人才资助，曾担任中国人工智能学会生物信息学与人工生命专业委员会副主任、中国科学信息科学青年编委、Genome Biology客座编委。主要从事人工智能与生命科学交叉的教学研究工作，发表学术论文200 余篇，授权发明专利30余项。构建的生物信息人工智能计算平台被广泛使用超过1千万次，理论预测结果被生物实验大量验证，揭示与促进了相关生命知识的新发现。曾获上海市青年科技杰出贡献奖、霍英东教育基金会青年教师奖等，指导毕业的研究生入选国家级青年人才、上海市优秀研究生学位论文奖、上海交通大学优秀博士学位论文奖等多人。
新能源柔直外送系统的宽频振荡特性分析和全驱阻尼控制
曹一家 教授
深圳大学，中国
摘要
新能源发电设备的大规模接入以及高压直流输电系统的多点互联，使新型电力系统呈现出高度复杂、非线性与强不确定性的特征，导致宽频振荡事件频繁发生，严重威胁系统的安全稳定运行。针对上述挑战，本报告将系统介绍近年来在以下方面的研究成果：宽频振荡与频率耦合机理分析、混叠型振荡源定位、宽频振荡全驱阻尼控制技术。
个人简介
我国智能电网与新能源并网技术领域的著名专家，享受政府特殊津贴专家，首批国家“万人计划”中青年科技创新领军人才、长江学者特聘教授、国家杰出青年基金获得者。长期从事智能电网基础理论与关键技术研究、新能源和储能系统并网运行与控制技术研究，提出了面向复杂电力系统全局优化理论、智能电网信息集成方法，研发了面向我国分散式新能源安全并网与高效消纳的关键技术与装备。获国家自然科学二等奖、国家科技进步二等奖、国家科学技术进步奖创新团队奖、湖南省最高成就奖-光召科技奖，以及省部级一等奖8项。
A Universal Decomposition of Distributed Optimization Algorithms in Graph Frequency Domain
柴利 教授
浙江大学，中国
摘要
In this talk, we introduce a universal decomposition for three typical first-order distributed optimization algorithms, namely EXTRA, DIGing and AugDGM. By using the graph Fourier transform (GFT). We show that the algorithm iteration can be divided into two subsystems, of which one represents the dynamics of the average state of all agents converging to the optimal solution, and another the dynamics of the high-frequency error subsystems converging to zeros, provided
that the whole algorithm converges. Different to existing decomposition methods, our method generates a partially decoupled structure, which shows that the convergence of the algorithm iteration is totally determined by the high-frequency error subsystem. Moreover, in the novel decomposition structure, the average state subsystems are exactly the same for three different algorithms. The differences among three algorithms are characterized by the high-frequency error subsystem. These observations enable new insights on the analysis and design of distributed optimization algorithms, about which we will also make a brief discussion.
个人简介
柴利，教授、国家杰出青年科学基金获得者、国务院特殊津贴专家。现为浙江大学控制学院求是特聘教授，校学术委员会委员。2008-2022年于武汉科技大学信息科学与工程学院工作，为首批“全国高校黄大年式教师团队”负责人，湖北省楚天学者特聘教授。曾获湖北省先进科技工作者、湖北省高等学校优秀共产党员等荣誉奖励。曾入选首批湖北省高端人才引领培养计划、湖北省新世纪高层次人才计划、教育部新世纪优秀人才支持计划。主要研究兴趣为智能自主系统、图信号处理与学习、分布式优化、网络化控制系统等。在IEEE TAC、TSP、TPAMI等国际知名期刊和会议发表论文100余篇。现为中国自动化学会CPS控制与决策专委会副主任委员等。
Intelligent Perception and Autonomous Avoidance of Spacecraft Confronting Orbital Threats
邱剑彬 教授
哈尔滨工业大学，中国
摘要
Spacecraft are high-value strategic assets, and their safe and stable in-orbit operation is the fundamental prerequisite for completing various tasks. Currently, the orbital space is becoming increasingly congested, with a sharp increase in collision risks. Space competition is intensifying, harassment is on the rise, and the number of threats continues to grow. The safe operation of spacecraft is facing severe challenges. At present, the orbital threats response measures heavily rely on ground support, featuring poor timeliness in handling threats and high operational control pressure, making it difficult to adapt to the deteriorating space situation. Therefore, it is urgent to develop the spacecraft’s autonomous avoidance ability against orbital threats and develop an integrated intelligent autonomous control system for orbital threat avoidance with an on-board closed-loop of “perception-decision-control”. This talk will introduce our research progress in recent years on the logical architecture analysis, modeling, and mission planning of the integrated control system for intelligent perception and autonomous avoidance of spacecraft confronting orbital threats.
个人简介
邱剑彬，哈尔滨工业大学航天学院教授/博士生导师，长期致力于智能控制理论与应用研究，获省部级自然科学一等奖4项、科技进步特等奖1项。入选国家级高层次人才、IEEE Fellow、全球高被引学者、德国洪堡学者等，担任《IEEE模糊系统汇刊》、《IEEE控制论汇刊》、《IEEE工业信息学汇刊》等国际著名期刊编委。
Hyperexponential stability and stabilization for uncertain nonlinear systems
刘允刚 教授
山东大学，中国
摘要
This talk discusses hyperexponential stability and hyperexponential stabilization for uncertain nonlinear systems. A definition of hyperexponential stability is first given in the widely-recognized manner. Its connections with the existing definitions of hyperexponential stability are identified. Necessary and sufficient conditions are then established to demonstrate the possibilities and impossibilities of pursuing hyperexponential stability. A time-varying-gain-based strategy is finally developed to achieve global hyperexponential stabilization for a class of uncertain nonlinear systems.
个人简介
山东大学二级教授、院学术委员会副主任、教育部重点实验室主任。长江学者特聘教授、国家杰出青年科学基金获得者、山东省泰山学者攀登计划入选者。曾获国家自然科学奖二等奖、第十届关肇直奖、中国自动化学会优秀博士学位论文指导教师奖、山东省优秀研究生指导教师奖、山东大学优秀教师奖、山东大学“我心中的好导师”等。现/曾任中国系统工程学会理事、中国人工智能学会自主无人系统专委会副主任委员、山东省电子学会常务理事及人工智能与机器视觉专委会主任等。主要研究领域：非线性控制、自适应控制、随机系统优化与控制、智能系统理论与方法、基于数据的智能控制方法与技术等。主持国家自然科学基金重点项目、山东省重大科技创新工程项目、山东省重大基础研究项目等。
Privacy-Preserving Control and Decision-Making
马倩 教授
南京理工大学，中国
摘要
With the advancement of technologies such as artificial intelligence and the Internet of Things, the need for data privacy protection is widespread in control and decision-making processes across both national defense and civilian domains, including weapon guidance, attack-defense games, intelligent transportation, and brain-computer interfaces. Information leakage and theft within control systems often lead to severe consequences, even affecting national security. This report focuses on control and decision-making under privacy protection. It introduces data privacy protection and privacy-preserving methods, as well as preliminary research progress by our team in dynamic asymptotic stabilization based on homomorphic encryption and distributed decision-making based on differential privacy.
个人简介
马倩，南京理工大学紫金卓越教授、博士生导师。2013年毕业于南京理工大学，获控制科学与工程博士学位。先后入选教育部长江学者奖励计划青年学者和特聘教授，主持国家自然科学基金重点项目、江苏省杰出青年基金等。研究方向为自主无人系统的控制与决策、隐私保护与数据安全，获国家自然科学二等奖、教育部自然科学一等奖、江苏省自然科学一等奖、中国自动化学会自然科学一等奖及中国自动化学会青年科学家奖。