SCI和EI收录∣中国化工学会会刊

Chin.J.Chem.Eng. ›› 2015, Vol. 23 ›› Issue (12): 1945-1950.DOI: 10.1016/j.cjche.2015.10.005

Previous Articles     Next Articles

Hellinger distance based probability distribution approach to performance monitoring of nonlinear control systems

Chen Li1,2, Biao Huang2, Feng Qian1   

  1. 1 Key Laboratory of Advanced Control and Optimization, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China;
    2 Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB T6G 2G6, Canada
  • Received:2015-05-19 Revised:2015-09-02 Online:2016-01-19 Published:2015-12-28
  • Contact: Feng Qian
  • Supported by:

    Supported by the National Natural Science Foundation of China (61134007, 61203157), the National Science Fund for Outstanding Young Scholars (61222303), the Fundamental Research Funds for the Central Universities (22A20151405) and Shanghai R&D Platform Construction Program (13DZ2295300).

Hellinger distance based probability distribution approach to performance monitoring of nonlinear control systems

Chen Li1,2, Biao Huang2, Feng Qian1   

  1. 1 Key Laboratory of Advanced Control and Optimization, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China;
    2 Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB T6G 2G6, Canada
  • 通讯作者: Feng Qian
  • 基金资助:

    Supported by the National Natural Science Foundation of China (61134007, 61203157), the National Science Fund for Outstanding Young Scholars (61222303), the Fundamental Research Funds for the Central Universities (22A20151405) and Shanghai R&D Platform Construction Program (13DZ2295300).

Abstract: Control performance monitoring has attracted great attention in both academia and industry over the past two decades. However, most research efforts have been devoted to the performance monitoring of linear control systems, without considering the pervasive nonlinearities (e.g. valve stiction) present inmost industrial control systems. In thiswork, a novel probability distribution distance based index is proposed tomonitor the performance of non-linear control systems. The proposedmethod uses Hellinger distance to evaluate change of control system performance. Several simulation examples are given to illustrate the effectiveness of the proposed method.

Key words: Control performance monitoring, Kernel density estimation, Hellinger distance, Nonlinear system

摘要: Control performance monitoring has attracted great attention in both academia and industry over the past two decades. However, most research efforts have been devoted to the performance monitoring of linear control systems, without considering the pervasive nonlinearities (e.g. valve stiction) present inmost industrial control systems. In thiswork, a novel probability distribution distance based index is proposed tomonitor the performance of non-linear control systems. The proposedmethod uses Hellinger distance to evaluate change of control system performance. Several simulation examples are given to illustrate the effectiveness of the proposed method.

关键词: Control performance monitoring, Kernel density estimation, Hellinger distance, Nonlinear system