报 告 人：张友民，加拿大康考迪亚大学（Concordia University）教授
报告题目：Condition Monitoring, Diagnosis, and Fault-Tolerant Control in Safety-Critical
Systems - with Applications to Renewable Engineering Systems and Smart Grids
内容简介：Condition monitoring, fault diagnosis, and fault-tolerant control (FTC) in safety-critical systems such as airplanes, nuclear power plants, chemical plants and cars etc., have been progressively and extensively investigated worldwide since the 1970’s. However, the two recent catastrophic accidents induced by the crashes of two Boeing 737 MAX8 airplanes have highlighted again the necessity and urgency for and fault diagnosis and FTC research & development and their industrial applications. The famous blackout that shut down the power in many of the American northeast areas in 2003 have also promoted the development of renewable energy and smart grids in recent years. Electrical microgrids with sustainable distributed power systems, in particular, wind power, are essential to provide service that is 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 and fault-tolerant control techniques at all levels of power generation, integration into grid, and distribution. In this talk, brief overall view on the challenges and latest developments on condition monitoring, fault detection and diagnosis (FDD), and fault-tolerant control (FTC), and fault-tolerant cooperative control (FTCC) in wind turbines, wind farm, and microgrids are given first. Our latest research works on the above-mentioned subjects will then be introduced as the second part of the talk.
报告人简介：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正教授。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、感知与避障、飞行器导航、制导与控制、多智能体/多运动体(空中、地面、水面、及风场)容错协同控制及其与遥感测量技术相结合进行森林防火与森林资源管理、电力巡线与监测、环境监测、以及搜救与救援等领域的研究与应用开发。张友民教授是国际上故障诊断与容错控制及无人机领域的知名学者。自1992年共发表500余篇杂志和会议论文及4本书籍。张友民教授曾作为大会主席主持并组织了1994年中国自动化学会青年学术年会。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)及“自主无人系统国际会议”(ISAS)。目前担任ICUAS的执行委员会委员、ISAS的指导委员会委员、“智能无人系统”学会(ISIUS)的副主席。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、国际杂志“智能机器人系统”资深编辑(Editor-at-Large)，IEEE Transactions on Neural Networks & Learning Systems及最新出版发行的三个与无人系统相关的国际杂志、包括“无人系统”、“国际智能无人系统杂志”、“无人系统技术”等多个国际杂志的编辑和编委。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，美国航空航天学会(AIAA)无人系统程序委员会委员，美国电气与电子工程师学会(IEEE)机器人与自动化协会空中机器人和无人驾驶技术委员会委员，美国机械工程师学会(ASME)/电气与电子工程师学会(IEEE)机电一体化技术、嵌入式系统和应用技术委员会委员，中国自动化学会“技术过程故障诊断与安全性”、“控制理论”、“过程控制”、“大数据”与“导航、制导与控制”专业委员会委员以及“可信控制”专业委员会副主任委员。
报 告 人：谢文芳，加拿大康考迪亚大学（Concordia University）教授
报告题目：Accuracy Enhancement of Industrial Robots Using Visual Servoing
内容简介：Industrial robots are widely used in various applications, from simple packaging tasks to the complex aerospace applications. Most of the manufacturing industries use serial robots for inspection, assembly, welding, drilling, riveting, palletizing and fastening. The relatively low absolute accuracy of industrial robots poses challenge for fulfilling these tasks with high precision demand. There are many factors which affect the accuracy of industrial robots including the manufacturing process, tolerances and inevitable inaccuracies of the components in an industrial robot and the operating environment disturbances. These factors cause the difference between the nominal model of the robot in the controller and the real one. Although robot calibration can improve the accuracy of robots with the help of complex mathematical algorithms and metrology equipment, the resulting accuracy is often insufficient and tends to be subjected to external disturbances. Installing secondary high-accuracy encoders at each robot joint, immediately after the gearbox can be costly and infeasible especially for large number of multiple DOF robots. In the project, two novel, cost-effective, fast and practical sensor-based correction algorithms are developed and implemented to enhance the absolute accuracy of industrial robots using visual servoing techniques. The research works includes on-line pose estimation, dynamic pose correction and dynamic path tracking. Extensive experimental testing on extensively on a FANUC serial robot demonstrated that accuracy of pose correction is enhanced to 0.050 mm for the position and 0.050º for the orientation and the positional and rotational tracking accuracy is improved to 0.1mm and 0.05 º.
报告人简介：Dr. Wen-Fang Xie is a full Professor with the Department of Mechanical, Industrial & Aerospace Engineering at Concordia University, Montreal, Canada. She was an Industrial Research Fellowship holder from Natural Sciences and Engineering Research Council of Canada (NSERC) before she joined Concordia University as an assistant professor in 2003, was promoted to Associate Professor in 2008 and full professor in 2014. She received her Ph.D from the Hong Kong Polytechnic University in 1999. Her research interests include identification and control in mechatronics, artificial intelligent control, advanced process control and robotic visual servoing. She has published over 200 journal and conference papers and has graduated over 10 Ph.D and 18 M.A.Sc students. She has received various grants including NSERC Discovery grant (since 2003), FQRNT (principal investigator), MDEIE International Research and Innovation Initiatives, NSERC CRD grant (twice), CFI leading edge. She has been an active member of many IEEE conference organizing committees. She is a CSME fellow and IEEE senior member. She is an Editorial Board member of Journal of Mechatronics and International Journal of Advanced Robotic Systems.