杰出讲座

Subhrakanti Dey 教授, 乌普萨拉大学, 瑞典

Ralph Kennel 教授, 慕尼黑工业大学, 德国

李永明 教授 辽宁工业大学，中国

摘要

  实际工程控制系统，如：航空航天系统，机器人系统以及化工过程系统等，日趋呈现出高度的非线性、大规模性、不确定性、多变量性以及强耦合性等综合特征，给传统的集中式控制理论和方法带来了挑战。分散控制通过局部自治、有限协调的方式，从根本上解决了大规模复杂系统在信息、计算和可靠性方面的瓶颈。因此，不确定非线性互联大系统的分散控制已成为应对现代复杂工程系统的核心方法之一。本报告针对典型的不确定非线性互联大系统，研究分散控制器的设计方法，以及控制系统的稳定性、收敛性和鲁棒性的证明等问题。

个人简介

  李永明 ，教授，博士生导师，辽宁工业大学副校长，国务院政府特殊津贴专家，国家自然科学基金青年科学基金A类、B类项目获得者。研究方向：智能控制理论及应用。主持国家自然科学基金联合重点项目、国家重点研发计划课题、辽宁省“揭榜挂帅”重大课题等20余项国家及省部级项目。发表论文100余篇，授权发明专利、软件著作权20余项。出版教材及专著4部。获教育部自然科学一等奖，辽宁省自然科学二等奖，中国自动化学会科技进步一等奖。

刘腾飞 教授, 东北大学, 中国

Girish Nair 教授, 墨尔本大学, 澳大利亚

George Rovithakis 教授 塞萨洛尼基亚里士多德大学, 希腊

摘要

  Networked Control Systems (NCSs) have become a fundamental architecture in modern control applications, where sensors, controllers, and actuators exchange information over shared communication networks. While this structure offers significant advantages in scalability, flexibility, and resource efficiency, it also introduces network-induced constraints and effects—such as delays, data losses, quantization, and asynchronous sampling—that can severely impair performance and threaten stability.
  Outside the NCS framework, prescribed performance control (PPC) provides a powerful and conceptually elegant approach for enforcing user-defined transient and steady-state performance characteristics in a broad class of uncertain nonlinear systems. Its key strengths lie in the development of low-complexity, model-free, and robust controllers.
  However, applying PPC within NCSs presents unique challenges due to the aforementioned network-induced effects, which can easily lead to internal instability. Addressing these challenges necessitates the development of robust PPC modifications tailored for networked environments.
  How exactly can this be achieved? Join me for the lecture to find out.

个人简介

  George A. Rovithakis is currently a Professor and Director of the Automation and Robotics Laboratory in the Department of Electrical and Computer Engineering at Aristotle University of Thessaloniki. His research interests include nonlinear control, robust adaptive control, prescribed performance control, robot control, and control-identification of uncertain systems using neural networks. He has authored or co-authored three books and over 190 papers published in scientific journals, conference proceedings, and book chapters.
  Professor Rovithakis is ranked among the top 2% of researchers worldwide by Stanford University, based on the impact of his published work. His research on trajectory-oriented prescribed performance guarantees—such as maximum overshoot, minimum convergence rate, and maximum steady-state error—in nonlinear closed-loop systems with uncertain dynamics led to the development of the Prescribed Performance Control (PPC) methodology.
  He currently serves as an Associate Editor for the IEEE Transactions on Automatic Control and has previously served as an Associate Editor for the IEEE Transactions on Neural Networks and the IEEE Transactions on Control Systems Technology. Additionally, he has been a member of the IEEE Control Systems Society Conference Editorial Board and the European Control Association (EUCA) Conference Editorial Board. Dr. Rovithakis is a member of the Technical Chamber of Greece, an elected member of EUCA, and a former Chair of the IEEE Greece Section Control Systems Chapter.

Ying Tan 教授, 墨尔本大学, 澳大利亚

Jun Yang 教授 拉夫堡大学, 英国

摘要

  Safety-critical control is significant for robotics and autonomous system (RAS) applications where safety is an utmost concern. Control barrier function (CBF)-based control has shown its promising potential and power in delivering formal safe property of RAS. The presence of disturbances has negative effects on CBF-based control, leading to formal safety guarantee violations and degraded control performance. In this lecture, we will introduce the background of safety-critical control, highlight the motivation why formal method is required, give a comprehensive tutorial on CBF-based control approaches, and elaborate the emerging methods on safety-critical disturbance rejection control and their applications to interactive robotics and autonomous cranes for port automation.

个人简介

  Jun Yang received the B.Sc. degree in automation from the Department of Automatic Control, Northeastern University, Shenyang, China, and the Ph.D. degree in control theory and control engineering from the School of Automation, Southeast University, Nanjing, China, in 2006 and 2011, respectively. He worked in School of Automation, Southeast University as Lecturer from 2011, Associate Professor from 2014, and Full Professor from 2018 all in Control Systems. Since 2020, he has been with the Department of Aeronautical and Automotive Engineering, Loughborough University, Loughborough, U.K., as a Senior Lecturer and is promoted to a Reader in 2023. He once held various academic visiting positions worldwide like Visiting Professor at Imperial College London (UK, 2019), Visiting Associate Professor at Nanyang Technological University (Singapore, 2016), and Visiting Research Fellows at RMIT University (Australia, 2015) and Western University of Sydney (Australia, 2013).
  His research interests include disturbance observer, motion control, mechatronics, robotics, and automation. Dr. Yang was the recipient of the EPSRC New Investigator Award. He serves as an Associate Editor or Technical Editor for IEEE Transactions on Automatic Control, IEEE Transactions on Industrial Electronics, IEEE-ASME Transactions on Mechatronics, etc. He is the founding Editor-in-Chief of Advanced Mechatronics since 2026, and Deputy Editor-in-Chief of Drones and Autonomous Vehicles since 2024. He is a Fellow of IEEE, IET, and AAIA.

张立宪 教授 哈尔滨工业大学，中国

摘要

  特种机器人是面向特殊、复杂、极端环境或任务，具备特定、专用功能的机器人。特种旋翼飞行器，也与消费级和工业级无人机不同，具有特种的构型、载荷、材质，结合旋翼飞行器的高机动性、空间可达性、可灵活部署等优势，在安防侦察、应急救援、极端环境作业等任务中具有不可替代的作用。本报告将介绍团队在旋翼式空地跨域无人机、空间站舱内飞行器等几类特种旋翼飞行器的构型、规划与控制方面的设计和实践工作，并展望其未来发展趋势。

个人简介

  张立宪 ，哈尔滨工业大学航天学院教授、博士生导师，国家杰出青年科学基金获得者、国家高层次人才，IEEE会士、IET会士。长期从事自动控制理论及应用研究，主持载人航天工程专项、国家重大科研仪器研制项目、某部委重点项目等科研项目30余项，在智能决策与控制，特种机器人、航天器自主控制等方向上发表Automatica、IEEE TAC/TAES/RAL、AIAA JGCD等高水平论文200余篇，获2023年度机器人领域权威期刊IEEE RAL最佳论文、2013年中国百篇最具国际影响学术论文；谷歌学术引用2万余次，连续10年入选全球高被引学者。作为总设计师，研发了中国首台空间站舱内机器人，被新年除夕黄金时段《新闻联播》等多次央视报道；所研平台在党和国家领导人出席的重要展览中展出。曾获钱学森杰出贡献奖，国家自然科学二等奖、黑龙江省自然科学一等奖(2项)。

赵延龙 教授, 中国科学院数学与系统科学研究院, 中国

更多杰出讲座尚在确认中，敬请期待！