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

  • 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.
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