The kalman particle swarm optimization algorithm and its application in soft-sensor of acrylonitrile yield

  • Authors:

  • Yufa Xu;Guochu Chen;Jinshou Yu

  • Affiliations:

  • Research Institute of Automation, East China University of Science and Technology, Shanghai, China;Research Institute of Automation, East China University of Science and Technology, Shanghai, China;Research Institute of Automation, East China University of Science and Technology, Shanghai, China

  • Venue:
  • ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part II
  • Year:
  • 2006

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Abstract

This paper proposes kalman particle swarm optimization algorithm (KPSO), which combines kalman filter with PSO. Comparison of optimization performance between KPSO and PSO with three test functions shows that KPSO has better optimization performance than PSO. The combination of KPSO and ANN is also introduced (KPSONN). Then, KPSONN is applied to construct a soft-sensor of acrylonitrile yield. After comparing with practical industrial data, the result shows that KPSONN is feasible and effective in soft-sensor of acrylonitrile yield.