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Multi-channel Spatio-Temporal Modeling for Hammerstein 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

A multi-channel spatio-temporal Hammerstein modeling approach is presented in this chapter. As a special case of the model described in Chapter 4, a spatio-temporal Hammerstein model is constructed with a static nonlinearity followed by a linear spatio-temporal kernel. When the model structure is matched with the system, a basic single-channel identification algorithm with the algorithm used in the Chapter 4 can work well. When there is unmodeled dynamics, a multi-channel modeling framework can provide a better performance, because more channels used can attract more information from the process. The modeling convergence can be guaranteed under noisy measurements. The simulation example and the experiment on snap curing oven are presented to show the effectiveness of this modeling method.

Keywords

Model Predictive Control Distribute Parameter System Unmodeled Dynamic Hammerstein Model Laguerre Function 
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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Copyright information

© Springer Netherlands 2011

Authors and Affiliations

  • Han-Xiong Li
    • Chenkun Qi

      There are no affiliations available

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