A Novel Spatiotemporal Fuzzy Method for Modeling of Complex Distributed Parameter Processes

Fuzzy modeling has been widely used to model lumped parameter systems. However, it cannot be used to model complex distributed parameter systems (DPS) due to its inability to handle spatial dynamics. In this paper, we propose a novel spatiotemporal fuzzy method for the modeling of complex nonlinear DPSs. A spatial fuzzy model is first constructed to represent the nonlinear spatial dynamics. This process ensures that the space information is inherently considered in the spatiotemporal fuzzy model. A fuzzy model is then used to represent the nonlinear temporal dynamics. These two fuzzy models are further integrated to construct a spatiotemporal fuzzy model, which allows for the reconstruction of the DPS. Additionally, it can improve the modeling robustness even in the presence of noise due to the robust ability of fuzzy modeling. Performance analyses and experimental validations further show that the proposed method can effectively model complex nonlinear DPSs and has the better modeling ability than several commonly used methods.

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