Parameter-coupled state space models based on quasi-Gaussian fuzzy approximation

被引:1
作者
Wang, Yizhi [1 ,2 ]
Ma, Fengyuan [1 ]
Tian, Xiaomin [1 ]
Chen, Weina [1 ]
Zhang, Yang [2 ]
Ge, Shanshan [1 ]
机构
[1] Jinling Inst Technol, Coll Intelligent Sci & Control Engn, Nanjing, Peoples R China
[2] Minjiang Univ, Fujian Key Lab Funct Marine Sensing Mat, Fuzhou 350108, Peoples R China
基金
中国国家自然科学基金;
关键词
Quasi-Gaussian Fuzzy Sets; Parameter-Coupled Models; Fuzzy Approximation; Pharmaceutical Equipment; State Space Models; SYSTEMS;
D O I
10.1038/s41598-024-77731-w
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:18
相关论文
共 34 条
[1]  
Akin C., 2024, Approx. Hypergroups Math., V12, P2445
[2]  
AL-Mahemmdi WD., 2023, Iraqi J. Sci, V64, P2946, DOI [10.24996/ijs.2023.64.6.23, DOI 10.24996/IJS.2023.64.6.23]
[3]   A Comparative Analysis of the Fractional-Order Coupled Korteweg-De Vries Equations with the Mittag-Leffler Law [J].
Aljahdaly, Noufe H. ;
Akgul, Ali ;
Shah, Rasool ;
Mahariq, Ibrahim ;
Kafle, Jeevan .
JOURNAL OF MATHEMATICS, 2022, 2022
[4]  
Andres-Sanchez D. J., 2017, Insurance Math. Econ., P7283
[5]   Performance optimization of a heat exchanger with coiled-wire turbulator insert by using various machine learning methods [J].
Celik, Nevin ;
Tasar, Beyda ;
Kapan, Sinan ;
Tanyildizi, Vedat .
INTERNATIONAL JOURNAL OF THERMAL SCIENCES, 2023, 192
[6]  
GWDALI R. S., 2023, Astron. Comput., V45
[7]   Disturbance rejection controller design based on nonlinear with fuzzy approximation technique for a tidal turbine system [J].
Hasan M.W. .
Journal of King Saud University - Engineering Sciences, 2023, 35 (08) :566-576
[8]   A new type of fuzzy systems using pyramid membership functions (PMFs) and approximation properties [J].
Jiang, Mingzuo ;
Yuan, Xuehai .
SOFT COMPUTING, 2018, 22 (21) :7103-7118
[9]  
Jiang Y., 2024, P 35 CHIN PROC CONTR, V7, P25
[10]   Additive Fuzzy Systems: From Generalized Mixtures to Rule Continua [J].
Kosko, Bart .
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2018, 33 (08) :1573-1623