会议名称(中文)： The 17th IFAC Symposium on System Identification
会议名称(英文)： The 17th IFAC Symposium on System Identification
所属学科： 人工智能,自动化技术应用,控制系统仿真技术
开始日期： 2015-10-19
结束日期： 2014-10-21
所在国家： 中华人民共和国
所在城市： 北京市 东城区
主办单位： 国际自动控制联合会、中国自动化学会
[ 重要日期 ]
摘要截稿日期： 2015-01-15
会议背景介绍：
SYSID 2015 is sponsored by the IFAC Technical Committee on Modeling, Identification and Sigal Processing, Academy of Mathematicis and Systems Science, Chinese Academy of Sciences, and Technical Committee on Control Theory, Chinese Association of Automation.
SYSID is organized every three years. The previous edition, SYSID 2012, was held in Brussels, Belgium. SYSID 2015 will be the second SYSID symposium to take place in Beijing, and the first one was in 1988.
The symposium covers all major aspects of system identification, experimental modelling, signal processing and adaptive control from theoretical and methodological developments to practical applications in a wide range of application areas. The aim of the meeting is to promote the research activities and the cooperation between researchers in these areas. To enhance the applications and industrial perspective of the symposium, participation of authors from industry is particularly encouraged.
Papers presented at SYSID 2015 will be hosted and freely available on-line on the IFAC-PapersOnLine.net website and will be citable via an ISSN and a DOI.
征文范围及要求：
It is the intention of the organizers to promote SYSID 2015 as a meeting place where scientists and engineers from several research communities can meet to discuss issues related to these areas. Relevant topics for the symposium program include:
Identifiability;
Identification of linear, nonlinear, time-varying, multivariable, hybrid and distributed systems;
Black-box modeling (neural networks, support vector machines, Kriging...);
Linear and nonlinear time series analysis;
Estimation from spatio-temporal data;
State estimation and parameter tracking;
Robustness issues in identification;
Sequential Monte Carlo methods, including particle filtering;
Learning, data mining and Bayesian approaches;
Parameter estimation and inverse modeling;
Modeling and identification of quantized systems;
Identification for control, adaptive control and data-based controller tuning;
Statistical analysis and uncertainty characterization;
Experiment design;
Model validation;
Monitoring and fault detection;
Applications (including but not limited to physical measurements, transportation, telecommunications, aerospace, automotive, process control, motion control, robotics, econometrics, modal analysis and structural health monitoring, bioengineering and medical systems, ecosystems, energy and information networks);
Teaching identification. |
