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Spatio-Temporal Modeling for Wiener Distributed Parameter Systems

  • Han-Xiong Li
  • Chenkun Qi
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 50)

Abstract

For Wiener distributed parameter systems (DPS), a spatio-temporal Wiener model (a linear DPS followed by a static nonlinearity) is constructed in this chapter. After the time/space separation, it can be represented by the traditional Wiener system with a set of spatial basis functions. To achieve a low-order model, the Karhunen-Loève (KL) method is used for the time/space separation and dimension reduction. Finally, unknown parameters of the Wiener system are estimated with the least-squares estimation and the instrumental variables method to achieve consistent estimation under noisy measurements. The simulation on the catalytic rod and the experiment on snap curing oven are presented to illustrate the effectiveness of this modeling method.

Keywords

Instrumental Variable Model Predictive Control Distribute Parameter System Transfer Function Matrix Instrumental Variable Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Springer Netherlands 2011

Authors and Affiliations

  • Han-Xiong Li
    • Chenkun Qi

      There are no affiliations available

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