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

Chen Li; Biao Huang; Feng Qian

doi:10.1016/j.cjche.2015.10.005

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

第25届中国过程控制会议专栏 | Updated：2026-01-06

- Hellinger distance based probability distribution approach to performance monitoring of nonlinear control systems
- Chinese Journal of Chemical Engineering Vol. 23, Issue 12, Pages: 1945-1950(2015)
- Affiliations：
  
  2 Department of Chemical and Materials Engineering, University of Alberta,, AB,Edmonton,Canada,T6G 2G6
- Author bio：
- Funds：
- DOI：10.1016/j.cjche.2015.10.005
  CLC：
- Published：2015
- Accepted：
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Chen Li, Biao Huang, Feng Qian. Hellinger distance based probability distribution approach to performance monitoring of nonlinear control systems[J]. Chin.J.Chem.Eng., 2015, 23(12): 1945-1950.
DOI：

Chen Li, Biao Huang, Feng Qian. Hellinger distance based probability distribution approach to performance monitoring of nonlinear control systems[J]. Chin.J.Chem.Eng., 2015, 23(12): 1945-1950. DOI： 10.1016/j.cjche.2015.10.005.

摘要

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.

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Related Institution

School of Energy and Environment, Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, Southeast University

Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Gliwise

2 College of Automation, Shenyang Institute of Engineering

3 State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology

4 State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University

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