Abstract
The use of hierarchical fuzzy systems (HFS) is an effective way to deal with the curse of dimensionality which is the main drawback for the application of fuzzy models in the modeling and control of large-scale systems. This paper proposes the design of HFS which implements T-S type cone fuzzy system (CFS). The performance of the hierarchical fuzzy system is evaluated through time series prediction and function approximation, which demonstrate that the proposed HFS working together with the optimization of parameters by genetic algorithm (GA) and k-means clustering in fuzzy partition provides structurally simple and accurate fuzzy models.
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Acknowledgements
Thanks to the support by National Natural Science Foundation of China (Nos. 51609110, 51779110 and 51809122).
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Jiang, Mz., Yuan, Xh., Wang, Jx. (2020). Design of Hierarchical Cone Fuzzy System for Nonlinear System Modeling. In: Cao, By. (eds) Fuzzy Information and Engineering-2019. Advances in Intelligent Systems and Computing, vol 1094. Springer, Singapore. https://doi.org/10.1007/978-981-15-2459-2_9
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DOI: https://doi.org/10.1007/978-981-15-2459-2_9
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