（一）

报告时间：11月15日（星期一）9:00

报告地点：信息楼自动化学院310报告厅、腾讯会议（ID: 171 337 408）

报 告 人：黄彪，加拿大阿尔伯塔大学（University of Alberta）教授

报告题目：Transfer Learning – Overview and Introduction

内容简介：With advance in computing power and multisensory technology, massive data accumulated can be processed by data-driven techniques to learn underlying driving forces and/or hidden patterns for better control of industrial processes. In order to train a data-driven model with satisfactory performance, sizable amounts of labelled data are required. However, it is often expensive, time consuming and labor-intensive to gather well-labelled data although massive data are being collected. It becomes even more demanding to collect such labelled data for an industrial plant under situations such as, when the plant has just started operation, the labels are hard to sample, or the labels are lab data that are sampled with considerable time delays. This is commonly referred to as the cold-start problem, where decisions have to be made while little or almost nothing has been known about the environment. In the context of the process industry, how to transfer the knowledge learned from some existing processes with well-labelled data into a related target process that has limited labels to establish a satisfactory model is the transfer learning. This presentation will give an overview and introduction to transfer machine from the machine learning perspective.

报告人简历：黄彪，1997年于阿尔伯塔大学过程控制专业获博士学位。1983和1986年于北京航空航天大学分别获得学士学位和硕士学位。1997年任阿尔伯塔大学化工与材料工程学院助理教授，目前为该学院的正教授，及油砂过程控制首席教授。IEEE Fellow、加拿大工程院院士、加拿大化学化工学会Fellow。获得包括德国洪堡学者奖，IFAC过程控制期刊最佳论文奖、APEGA卓越研究高峰奖、加拿大Bantrel设计与工业实践奖等。出版科研专著5部，发表300多篇SCI期刊论文。研究领域主要包括过程控制、数据解析，机器学习、贝叶斯推理。现担任IFAC Journal Control Engineering Practice主编，Journal of the Franklin Institute的领域编辑，以及Journal of Process Control的副编。

（二）

报告时间：11月15日（星期一）10:00

报告地点：信息楼自动化学院310报告厅、腾讯会议（ID: 171 337 408）

报 告 人：张友民，加拿大康考迪亚大学（Concordia University）教授

报告题目：Towards Safer and More Resilient Cyber-Physical Systems with Applications to

                     Smart Grids and Unmanned Systems

内容简介：Condition monitoring, fault detection and diagnosis (FDD), and fault-tolerant control (FTC) in traditional safety-critical systems, such as airplanes, nuclear power plants, chemical plants and cars etc. have been progressively and extensively investigated worldwide.Electrical microgrids with sustainable distributed power systems are essential to provide services that are optimal, reliable, cost effective, and environmentally responsible. One of key techniques for ensuring the viability and effectiveness of microgrids is to make use of advanced condition monitoring, FDD and FTC techniques at all levels of power generation, integration into grid, distribution through networks, and also the recent trend for handling cyber-attacks in such type of cyber-physical systems (CPS). In this talk, a brief overall view on the challenges and latest developments on condition monitoring, fault/attack detection and diagnosis, FTC, and fault-tolerant cooperative control (FTCC) in smart grids (with renewable wind and solar energies) and unmanned systems (with air, land, marine vehicles) are given first. Our latest research works on the above-mentioned subjects will then be introduced as examples among recently fast-developing research works in the field.

报告人简历：张友民博士是加拿大康考迪亚大学机械、工业与航空工程系及康考迪亚航空设计与创新研究所终身教授。是加拿大机械工程师学会(CSME)会士(Fellow)，AIAA和IEEE高级会员。张友民教授长期从事控制理论与工程应用方面的研究与开发工作，专长于故障检测与诊断、容错控制、环境监测、以及搜救与救援等领域的研究与应用开发。自2013年以来多次作为大会主席、大会协主席、大会程序委员会主席，参与并组织“无人机系统国际会议”(ICUAS)、“智能无人系统国际会议”(ICIUS)等会议。目前担任“国际智能无人系统”协会(ISIUS)主席(President)、ICUAS的执行委员会委员、ISAS的指导委员会委员。张友民教授曾任国际杂志“仪表、自动化与系统”的创刊主编(Editor-in-Chief)并目前担任荣誉主编、担任国际杂志“Journal of Intelligent & Robotic Systems”理事会成员和北美区域负责人(Board Member of Governors and Regional Representative (North America))以及“IEEE Transactions on Neural Networks & Learning Systems”等多个杂志期刊的编辑和编委。并担任国际自动控制联合会(IFAC)故障检测、监控和安全的技术过程技术委员会委员等。

（三）

报告时间：11月15日（星期一）11:00

报告地点：信息楼自动化学院310报告厅、腾讯会议（ID: 171 337 408）

报 告 人：谢立华，新加坡南洋理工大学（Nanyang Technological University）教授

报告题目：Network Localization and Formation Maneuver Control  

内容简介：Networked systems have attracted recurring research interests from the control community due to its extensive applications in civil and military areas. Most research interests on networked systems revolve around two fundamental problems, that is, localization and control, where localization serves as the underpinning of control strategies. In this talk, we discuss the distributed localization of large-scale networks with various types of measurements. A general distributed localization framework is proposed, where the local coordinate frames of different nodes have different unknown orientations. An angle-displacement rigidity theory is developed to explore algebraic condition and graph condition of network localizability and a distributed localization protocol is proposed. The proposed method unifies local-relative-measurement-based distributed localization approaches and can be applied in both generic and non-generic configurations with an unknown global coordinate frame in both 2-D and 3-D spaces. We also look into the problem of steering a group of agents to maneuver as a whole so that they can respond to environment dynamics by changing the geometric pattern, translation, orientation, and scale of the formation continuously.

报告人简历：谢立华，新加坡南洋理工大学电气与电子工程学院教授，新加坡工程院院士，IEEE、IFAC和CAA会士。研究领域包括鲁棒控制、网络控制、定位与无人系统。曾出版了9本书，480多篇期刊文章，20项专利和技术披露。自2014年以来，他每年都被Thomson Reuters和Clarivate Analytics 列为高被引作者。他目前是《无人系统》杂志的主编和中国科学-信息科学杂志的副主编，曾是IET控制系列丛书主编，IEEE Transactions on Automatic Control, Automatica, IEEE Transactions on Control System Technology, IEEE Transactions on Control of Network Systems 等杂志的副主编。同时也是IEEE杰出讲师（2011-2014）和IEEE控制系统学会理事（2016-2018）。