Intelligence & Robotics第四次前沿论坛会议邀请 | 复杂系统的智能、优化与安全

由Intelligence & Robotics（IR）期刊主导的第四期前沿论坛有幸邀请到了上海交通大学的陈宏田副教授和上海大学的张进教授作为主讲人，将于  2023 年 3 月 28 日 20:00（北京时间）在 Zoom 平台正式召开。本期报告的主题是 Intelligence, Optimization, and Safety for Complex Systems，将由 IR 副主编上海大学彭晨教授担任主持人，全程采用中文进行。IR 编辑部期待您与来自世界各地的专家学者分享和交流最前沿的学术报告，促进领域的进一步发展，欢迎各位学者专家积极参会，交流讨论。

参会信息

报告题目：Intelligence, Optimization, and Safety for Complex Systems

时间：2022 年 3 月 28 日 周二 20:00（北京时间）

地点：Zoom 会议

ID: 846 2638 7855

会议主持

IR 副主编 彭晨教授

上海大学机电工程与自动化学院副院长、教授、博士生导师

国家百千万人才工程、有突出贡献中青年专家、上海市“东方学者”、“东方学者跟踪计划”、“浦江人才计划”、2020-2022 年全球高被引科学家、2014-2022 年 Elsevier 中国高被引学者入选者。彭教授主持国家重点研发项目 1 项，国家自然基金项目 6 项（其中 1 项重点），工信部课题 1 项，省部级项目 20 余项。主要研究领域包括网络化控制、安全控制；鲁棒控制、模糊系统、时滞系统分析与综合；流程供应链优化与调度；工业炉窑能效优化；流程工业智能故障诊断与监测等。任 IEEE 高级会员、IEEE-PES 智慧物联与控制分委会主席、美国《数学评论》评论员、上海市电子电器技术协会副理事长、上海市自动化应用专委会主任，IEEE Transactions on Industrial Informatics、Information Sciences 等国际期刊的编委。

特邀演讲嘉宾

IR 副主编 陈宏田博士上海交通大学自动化系副教授，博士生导师

IEEE 会员。本硕毕业于南师大，博士毕业于南京航空航天大学。2018 年在德国先进控制与复杂系统研究所做访问学者。主要研究方向为数据驱动技术、人工智能、量子计算、分布式系统等及其在高速列车牵引系统的故障诊断应用。目前为止，发表英文专著 1 部，国际英文论文 40 余篇（IEEE 汇刊 18 篇）、授权与受理国家专利 8 项。主持、参与国家级和省部级项目 6 项。获得中国自动化学会优秀博士论文奖、江苏省优秀博士论文奖、工信部创新特等奖（全校第一名），群星创新大奖、临近空间杯一等奖等多项个人奖与团体奖。目前为多个国际期刊客座编委、青年编委。受邀作为组织主席，举办 ICRCA 2022 国际会议与 AMEE 2022 国际会议；并承担 DDCLS 22 大会与 DOCS22 大会专题主席。

报告主题：Explainable Fault Diagnosis: A Bridge Between Unsupervised and Supervised Learning-based Fault Diagnosis Approaches

The increased complexity and intelligence of automation systems require the development of intelligent fault diagnosis (IFD) methodologies. By relying on the concept of a suspected space, this study develops explainable data-driven IFD approaches for nonlinear dynamic systems. More in detail, we parameterize nonlinear systems through a generalized kernel representation used for system modeling and the associated fault diagnosis. An important result obtained is a unified form of kernel representations, applicable to both unsupervised and supervised learning. More importantly, through a rigorous theoretical analysis we discover the existence of a bridge (i.e., a bijective mapping) between some supervised and unsupervised learning-based entities. Notably, the designed IFD approaches achieve the same performance by the use of this bridge. In order to have a better understanding of the results obtained, unsupervised and supervised neural networks are chosen as the learning tools to identify generalized kernel representations and design the IFD schemes; an invertible neural network is then employed to build the bridge between them. This report is a perspective talk, whose contribution lies in proposing and detailing the fundamental concepts for explainable intelligent learning methods, contributing to system modeling and data-driven IFD designs for nonlinear dynamic systems.

张进博士

上海大学机电工程与自动化学院教授、博士生导师

上海海外高层次人才计划入选者，现为上海大学机电工程与自动化学院教授、博士生导师。先后主持或参与包括国家自然科学基金、以色列科学基金、以色列高等教育委员会科研专项等在内的 8 项科学研究基金项目，在国内外重要学术期刊上发表论文 30 余篇，并担任 20 余种 SCI 学术期刊审稿人。

报告主题：Vibrational control with square wave dithers: A time-delay approach

This talk is concerned with stabilization problem of second-order systems by fast-varying square wave dithers depending on a small parameter. We first employ the known in vibrational control coordinate transformation that allows to cancel the high-gain term due to the introduced controller, and then present a time-delay approach to periodic averaging of the system in new coordinates. The resulting time-delay system is a perturbation of the averaged system in new coordinates which is assumed to be exponentially stable. The stability of the time-delay system guarantees the stability of the original system. We construct an appropriate Lyapunov functional for finding sufficient stability conditions in the form of linear matrix inequalities (LMIs). The upper bound on the small parameter that preserves the exponential stability is found from LMIs. Finally, two numerical examples including vibrational control of suspended pendulum illustrate the efficiency of the method.

欢迎广大学者积极参加此次会议，同时特刊Intelligence, Optimization, and Safety for Complex Systems开放征稿中，欢迎各位学者踊跃投稿！

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