Academic Journal
Parameter-coupled state space models based on quasi-Gaussian fuzzy approximation
| Title: | Parameter-coupled state space models based on quasi-Gaussian fuzzy approximation |
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| Authors: | Yizhi Wang, Fengyuan Ma, Xiaomin Tian, Weina Chen, Yang Zhang, Shanshan Ge |
| Source: | Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024) |
| Publisher Information: | Nature Portfolio, 2024. |
| Publication Year: | 2024 |
| Collection: | LCC:Medicine LCC:Science |
| Subject Terms: | Quasi-Gaussian Fuzzy Sets, Parameter-Coupled Models, Fuzzy Approximation, Pharmaceutical Equipment, State Space Models, Medicine, Science |
| More Details: | Abstract The accuracy of a fuzzy system’s approximation is closely tied to the performance of fuzzy control systems design, while this system’s interpretability depends on the description of a mechanical model using human language. This research introduces a quasi-Gaussian membership function characterized by a pair of parameters to achieve the sensitivity of a triangular membership function along with the interpretability of Gaussian membership functions. Consequently, a two-dimensional (2-D) quasi-Gaussian membership function is derived, and a method for establishing quasi-Gaussian fuzzy systems (QGFS) using a rectangular grid is proposed. After validating the approximation properties using the sine function for the one-dimensional (1-D) and 2-D QGFS, the systems are applied to approximate the depyrogenation tunnel, a significant piece of equipment in the pharmaceutical industry with various mechanical designs. Validation results indicate that the 1-D and 2-D QGFS can achieve an approximation error varying within a ± 5% range. Meanwhile, the 1-D and 2-D QGFSs are applied to mechanical models of the depyrogenation tunnel with satisfactory final approximation results. Lastly, the 2-D QGFS is capable of demonstrating an excellent description of models with coupled parameters. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 2045-2322 |
| Relation: | https://doaj.org/toc/2045-2322 |
| DOI: | 10.1038/s41598-024-77731-w |
| Access URL: | https://doaj.org/article/320d1a2878fb4e51ad9b960c41a8e11f |
| Accession Number: | edsdoj.320d1a2878fb4e51ad9b960c41a8e11f |
| Database: | Directory of Open Access Journals |
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| ISSN: | 20452322 |
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| DOI: | 10.1038/s41598-024-77731-w |
| Published in: | Scientific Reports |
| Language: | English |