文献类型：期刊文献

英文题名：Robust Fault Detection for a Class of Uncertain Nonlinear Systems Based on Multiobjective Optimization

作者：Yan, Bingyong[1];Wang, Huifeng[1];Wang, Huazhong[1]

机构：[1]E China Univ Sci & Technol, Dept Automat, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China

年份：2015

卷号：2015

外文期刊名：MATHEMATICAL PROBLEMS IN ENGINEERING

收录：;EI(收录号：20153801284079);WOS:【SCI-EXPANDED(收录号:WOS:000361289300001)】；

基金：This work is supported by National Natural Science Foundation of China (nos. 51407078, 61201124) and Special Fund of East China University of Science and Technology for Basic Scientific Research (WJ1313004-1, WH1114027, H200-4-13192, and WH1414022).

语种：英文

外文关键词：Nonlinear systems - Multiobjective optimization - Robust control

摘要：A robust fault detection scheme for a class of nonlinear systems with uncertainty is proposed. The proposed approach utilizes robust control theory and parameter optimization algorithm to design the gain matrix of fault tracking approximator (FTA) for fault detection. The gain matrix of FTA is designed to minimize the effects of system uncertainty on residual signals while maximizing the effects of system faults on residual signals. The design of the gain matrix of FTA takes into account the robustness of residual signals to system uncertainty and sensitivity of residual signals to system faults simultaneously, which leads to a multi objective optimization problem. Then, the detectability of system faults is rigorously analyzed by investigating the threshold of residual signals. Finally, simulation results are provided to show the validity and applicability of the proposed approach.