?!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"> Robust Analysis of Consensus Algorithms-上海大学机电工程与自动化学院
<xmp id="k9g6r"><tt id="k9g6r"></tt>

  • <th id="k9g6r"><address id="k9g6r"></address></th>
  •          
     
       
    -->
    首页 --> 公告通知

    Robust Analysis of Consensus Algorithms

    创建时间?nbsp; 2019-12-31  王智?    浏览次数?/span>


    报告时间?020??2?(周日)10:00-11:00   

    报告地点:宝山校区机自大?02B


    报告? 纪成? 博士, 约翰霍普金斯大学

    邀请人: 任肖?教授


    Title: Robust Analysis of Consensus Algorithms


    Abstract: A fundamental problem in the networked dynamical system is to achieve the consensus in the presence of disturbance. In this talk, we present our recent progress towards developing distributed control strategies for the design of consensus systems. Our approach is to analytically evaluate the robust performance through the input-output norm of the dynamical system. A parametrized family of consensus algorithms is studied. In particular, we show that the input-output norm is finite unless the zero eigenvalue of the system is not observable from the output. Two special consensus applications, vehicle collision potential and sensor failure contingency analysis, are presented to illustrate our approach. We further propose two easy-to-implement approaches to improve consensus performance. In the first approach, which is referred to as the augmented consensus algorithm, a consensus filter is introduced in the feedback loop that transfers the consensus-oriented estimation to the system. In the second approach, which is referred to as the robust consensus algorithm, we add time-relative feedback from the current state to the initial state.


    Bio: Chengda Ji graduated from a joint program and received his Bachelor of Engineering and Bachelor of Science degrees in Mechanical Engineering from Beijing Institute of Technology, China, and Polytechnic University of Turin, Italy, respectively, in 2016. He then joined the Department of Mechanical Engineering at Johns Hopkins University as a research assistant with Professor Dennice Gayme as his Ph.D. advisor. His research interests include modeling, dynamics, and control of networked systems, e.g., power systems, vehicle platoons, and computer networks.  His current research focuses on developing distributed control and learning frameworks for networked systems. Chengda was awarded the Johns Hopkins Graduate Fellowship (2017) and CSC Undergraduate Fellowship (2015).






    上一条:Dynamic Droop Control in Low-inertia Power Systems
    下一条:111引智基地讲坛?5?Topic: Applications & Future Trends of Advanced Industrial Robots



    版权所?© 上海大学   沪ICP?9014157   沪公网安?1009102000049?/span>  地址:上海市宝山区上大路99?nbsp;  邮编?00444   电话查询  
    技术支持:
    上海大学信息化工作办公室   联系我们   

    11ѡ忪