An Algorithm for Fault Detection in Stochastic Non-linear State-Space Models Using Particle Filters

摘要：

We propose a novel model-based algorithm for fault detection in nonlinear and non-Gaussian systems. The algorithm utilizes particle filters to generate a sequence of hidden states, which are then used in a log-likelihood ratio test to detect faults. The state-space models considered in this article are not easily amenable to standard log-likelihood ratio test, hence, a novel test statistic based on the joint likelihood function of hidden states and measurements is proposed. The proposed scheme is illustrated through an implementation on a highly non-linear multi-unit chemical reactor system.

作者: F. Alrowaie K.E. Kwok R.B. Gopaluni

作者单位: Department of Chemical and Biological Engineering,The University of British Columbia, Vancouver, V6T 1Z3, Canada

会议类型: 国际会议

会议名称: 2011 International Symposium on Advanced Control of Industrial Processes(2011工业过程先进控制技术国际研讨会)

会议地点: 杭州

会议语种:英文

页码: 60-65

在线出版日期: 2011-05-01（万方平台首次上网日期，不代表论文的发表时间）