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)


A spatio-temporal Hammerstein modeling approach is presented in this chapter. To model the nonlinear distributed parameter system (DPS), a spatio-temporal Hammerstein model (a static nonlinearity followed by a linear DPS) is constructed. After the time/space separation, it can be represented by the traditional Hammerstein 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. Then a compact Hammerstein model structure is determined by the orthogonal forward regression, and their unknown parameters are estimated with the least-squares method and the singular value decomposition. The simulation and experiment are presented to show the effectiveness of this spatio-temporal modeling method.


Model Predictive Control Distribute Parameter System Hammerstein Model NARX Model Hammerstein System 
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© Springer Netherlands 2011

Authors and Affiliations

  • Han-Xiong Li
    • Chenkun Qi

      There are no affiliations available

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