报告题目：Smart Control Engineering by Digital Twins and AI（数字孪生和AI驱动的智能控制工程）

报告时间：2024/12/29（星期日）10:00-11:30

报告地点：创新港巨构2-2072

报告学者：YangQuan Chen教授

报告人简介：

YangQuan Chen earned his Ph.D. from Nanyang Technological University, Singapore, in 1998. He had been a faculty of Electrical Engineering at Utah State University (USU) from 2000-12. He joined the School of Engineering, University of California, Merced (UCM) in summer 2012 teaching “Mechatronics”, “Digital Twins”, “Engineering Service Learning” and “Unmanned Aerial Systems” for undergraduates; “Fractional Order Mechanics”, “Linear Multivariable Control”, “Nonlinear Controls” and “Advanced Controls: Optimality and Robustness” for graduates. His research interests include mechatronics for sustainability, cognitive process control (smart control engineering enabled by digital twins), small multi-UAV based cooperative multi-spectral “personal remote sensing”, applied fractional calculus in controls, modeling and complex signal processing; distributed measurement and control of distributed parameter systems with mobile actuator and sensor networks. He received Research of the Year awards from USU (2012) and UCM (2020). He was listed in Highly Cited Researchers by Clarivate Analytics in 2018-2021. His lab website is http://mechatronics.ucmerced.edu/and his publication list is at https://scholar.google.com/citations?user=RDEIRbcAAAAJ&hl=en (Email: ychen53@ucmerced.edu) .

报告简介：

Experienced control engineers and researchers agree that before we design a controller we need to ask two questions 1) “What do we have/know?” and 2) “What do we want?” and after we have designed a controller, we also need to ask two questions 1) “How optimal?” and 2) “How robust?” Now, with the emerging wave of “Digital Transformation” such as Industry 4.0, I promote to ask the third question: “How smart?” This talk suggests a new frontier for control engineering: SCE - Smart Control Engineering and I will show that digital twins (DT) are the enabler towards SCE, a consequence of IAI (industrial artificial intelligence). By “smartness”, following the notion of US NSF program on S&AS (smart and autonomous systems), we signify the following 5 attributes 1) Taskable; 2) Cognitive; 3) Reflective; 4) Ethical; 5) Knowledge-rich. In this talk, we will show a case study to illustrate the SCE enabled by DT using IAI. This talk will also give a landscape overview of AI and DT in general and the most recent US DOE FASST (Frontiers in Artificial Intelligence for Science, Security and Technology) initiatives in particular.