Fault Diagnosis of Nonlinear Systems Based on Hybrid PSOSA Optimization Algorithm

Ling-Lai Li Dong-Hua Zhou Ling Wang

Ling-Lai Li, Dong-Hua Zhou, Ling Wang. Fault Diagnosis of Nonlinear Systems Based on Hybrid PSOSA Optimization Algorithm[J]. 国际自动化与计算杂志(英)/International Journal of Automation and Computing, 2007, 4(2): 183-188. doi: 10.1007/s11633-007-0183-4
引用本文: Ling-Lai Li, Dong-Hua Zhou, Ling Wang. Fault Diagnosis of Nonlinear Systems Based on Hybrid PSOSA Optimization Algorithm[J]. 国际自动化与计算杂志(英)/International Journal of Automation and Computing, 2007, 4(2): 183-188. doi: 10.1007/s11633-007-0183-4
Ling-Lai Li, Dong-Hua Zhou and Ling Wang. Fault Diagnosis of Nonlinear Systems Based on Hybrid PSOSA Optimization Algorithm. International Journal of Automation and Computing, vol. 4, no. 2, pp. 183-188, 2007. doi: 10.1007/s11633-007-0183-4
Citation: Ling-Lai Li, Dong-Hua Zhou and Ling Wang. Fault Diagnosis of Nonlinear Systems Based on Hybrid PSOSA Optimization Algorithm. International Journal of Automation and Computing, vol. 4, no. 2, pp. 183-188, 2007. doi: 10.1007/s11633-007-0183-4

Fault Diagnosis of Nonlinear Systems Based on Hybrid PSOSA Optimization Algorithm

doi: 10.1007/s11633-007-0183-4
基金项目: 

This work was supported by Natural Sciences Foundation of PRC (No.60574084);National 863 Project (No.2006AA04Z428 );the National 973 Program of PRC (No.2002CB312200).

Fault Diagnosis of Nonlinear Systems Based on Hybrid PSOSA Optimization Algorithm

Funds: 

This work was supported by Natural Sciences Foundation of PRC (No.60574084);National 863 Project (No.2006AA04Z428 );the National 973 Program of PRC (No.2002CB312200).

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出版历程
  • 收稿日期:  2006-03-15
  • 修回日期:  2006-12-30
  • 刊出日期:  2007-04-15

Fault Diagnosis of Nonlinear Systems Based on Hybrid PSOSA Optimization Algorithm

doi: 10.1007/s11633-007-0183-4
    基金项目:

    This work was supported by Natural Sciences Foundation of PRC (No.60574084);National 863 Project (No.2006AA04Z428 );the National 973 Program of PRC (No.2002CB312200).

摘要: Fault diagnosis of nonlinear systems is of great importance in theory and practice, and the parameter estimation method is an effective strategy. Based on the framework of moving horizon estimation, fault parameters are identified by a proposed intelligent optimization algorithm called PSOSA, which could avoid premature convergence of standard particle swarm optimization (PSO) by introducing the probabilistic jumping property of simulated annealing (SA). Simulations on a three-tank system show the effectiveness of this optimization based fault diagnosis strategy.

English Abstract

Ling-Lai Li, Dong-Hua Zhou, Ling Wang. Fault Diagnosis of Nonlinear Systems Based on Hybrid PSOSA Optimization Algorithm[J]. 国际自动化与计算杂志(英)/International Journal of Automation and Computing, 2007, 4(2): 183-188. doi: 10.1007/s11633-007-0183-4
引用本文: Ling-Lai Li, Dong-Hua Zhou, Ling Wang. Fault Diagnosis of Nonlinear Systems Based on Hybrid PSOSA Optimization Algorithm[J]. 国际自动化与计算杂志(英)/International Journal of Automation and Computing, 2007, 4(2): 183-188. doi: 10.1007/s11633-007-0183-4
Ling-Lai Li, Dong-Hua Zhou and Ling Wang. Fault Diagnosis of Nonlinear Systems Based on Hybrid PSOSA Optimization Algorithm. International Journal of Automation and Computing, vol. 4, no. 2, pp. 183-188, 2007. doi: 10.1007/s11633-007-0183-4
Citation: Ling-Lai Li, Dong-Hua Zhou and Ling Wang. Fault Diagnosis of Nonlinear Systems Based on Hybrid PSOSA Optimization Algorithm. International Journal of Automation and Computing, vol. 4, no. 2, pp. 183-188, 2007. doi: 10.1007/s11633-007-0183-4
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