Multiple ARX Model Based Identification for Switching/Nonlinear Systems with EM Algorithm

• Author / Creator

  Jin, Xing

• Two different types of switching mechanism are considered in this thesis; one is featured with abrupt/sudden switching while the other one shows gradual changing behavior in its dynamics. It is shown that, through the comparison of the identification results from the proposed method and a benchmark method, the proposed robust identification method can achieve better performance when dealing with the data set mixed with outliers.

  To model the switched systems exhibiting gradual or smooth transition among different local models, in addition to estimating the local sub-systems parameters, a smooth validity (an exponential function) function is introduced to combine all the local models so that throughout the working range of the gradual switched system, the dynamics of the nonlinear process can be appropriately approximated. Verification results on a simulated numerical example and CSTR process confirm the effectiveness of the proposed Linear Parameter Varying (LPV) identification algorithm.

• Subjects / Keywords

  • EM Algorithm
  • Switching Systems
  • System Identification

• Graduation date

  Spring 2010

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R31T4Z

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.