报告题目: Learning, Optimization and Control Co-Design for Real-time Systems: A Cyber-physical Systems Perspective

时间：2017年6月5日上午10:00

地点：主楼C2-401会议室

报告摘要: With the advances of mechanics, electronics, computer engineering, using autonomous robots, or a collection of them, to perform various tasks is becoming increasingly popular in both industry and our daily lives. Control plays an important role for stable and accurate task execution while learning is outstanding in dealing with unknowns or uncertainties. Recent advances in machine learning provides us with an opportunity to employ innovative learning structures for efficient adaptation. However, it remains challenging on how to efficiently integrate learning with control for real-time steering of systems with provable and guaranteed stability even in the worst case. This talk will present our recent results along this research direction and also show the construction of systems to support the autonomy of robots.

报告人简介:

李帅于美国史蒂文斯大学（Stevens Institute of Technology-美国国家级研究型私立大学，两位诺贝尔奖获得者母校，国际机械工程师协会ASME诞生地，美国四大理工名校之一）博士毕业后进入香港理工大学工作，作为核心成员参与组建嵌入式与物理信息系统实验室，并主导了搭设用于系统验证的多种机器人平台与用于软件定义可重构电源平台。长期从事非线性大系统估计与控制理论、神经网络智能控制，以及基于稳定性理论的传感器网络定位、多机器人协作、机械臂精确控制等方向的研究，取得了一系列具有国际影响的创新性成果。

累计发表论文近百篇，期刊论文逾60篇（IEEE Transactions论文30余篇），大部分为第一作者或通信作者，包括控制论与人工智能领域国际顶级期刊，如IEEE Transactions on Automatic Control (TAC)、IEEE Transactions on Neural Networks and Learning Systems (TNNLS)、IEEE Transactions on Cybernetics (TC)、IEEE Transactions on Industrial Electronics (TIE)等。在International Conference on Robotics and Automation, American Control Conference等控制领域重要国际会议发表论文20篇，相关研究成果得到了国际学术界的广泛关注和高度评价，并应邀参编英文专著3本，系统阐述相关研究成果。近5年论文被国内外同行引用923次，H-index为18。

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自动化工程学院