Modeling of Distributed Parameter Systems: Overview and Classification

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


This chapter provides a systematic overview of the distributed parameter system (DPS) modeling and its classification. Three different problems in DPS modeling are discussed, which includes model reduction for known DPS, parameter estimation for DPS, and system identification for unknown DPS. All approaches are classified into different categories with their limitations and advantages briefly discussed. This overview motivates us to develop new methods for DPS modeling.


Model Reduction Finite Difference Method Partial Differential Equation Sensor Number Distribute Parameter System 
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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  • Han-Xiong Li
    • Chenkun Qi

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