用必要的算术乘法运算求解任意耦合梯形全模糊Sylvester矩阵方程

IF 1.3 Q2 MATHEMATICS, APPLIED
A. Elsayed, N. Ahmad, G. Malkawi
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引用次数: 0

摘要

在许多应用中,特别是在分析控制系统的稳定性时,需要同时求解一对Sylvester矩阵方程(CSME)。然而,在某些情况下,在控制系统的稳定性分析中,crisp cme不能很好地处理不确定性问题。因此,本文提出了一种求解任意耦合梯形全模糊Sylvester矩阵方程(ACTrFFSME)的新方法。提出了一种新的模糊乘法运算方法,并将其应用于将ACTrFFSME转化为一个简化的非线性方程组。然后将其转化为一个绝对方程组,通过求解该方程组得到任意模糊解。该方法可以求解任意模糊方程,如全模糊矩阵方程、三角形和梯形模糊数的Sylvester和Lyapunov全模糊矩阵方程等。我们通过两个数值算例来说明所提出的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Solving Arbitrary Coupled Trapezoidal Fully Fuzzy Sylvester Matrix Equation with Necessary Arithmetic Multiplication Operations
A couple of Sylvester matrix equations (CSME) are required to be solved simultaneously in many applications, especially in analysing the stability of control systems. However, there are some situations in which the crisp CSME are not well equipped to deal with the uncertainty problem during the stability analysis of control systems. Thus, this paper proposes a new method for solving Arbitrary Coupled Trapezoidal Fully Fuzzy Sylvester Matrix Equation (ACTrFFSME). New arithmetic fuzzy multiplication operations are developed and applied to convert the ACTrFFSME to a reduced system of non-linear equations. Then it is converted to a system of absolute equations where the arbitrary fuzzy solution is obtained by solving that system. The proposed method can solve many arbitrary fuzzy equations, such as fully fuzzy matrix equations, Sylvester and Lyapunov fully fuzzy matrix equations with triangular and trapezoidal fuzzy numbers without any restrictions. We illustrate the proposed method by solving two numerical examples.
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来源期刊
CiteScore
2.30
自引率
0.00%
发文量
13
审稿时长
40 weeks
期刊介绍: Fuzzy Information and Engineering—An International Journal wants to provide a unified communication platform for researchers in a wide area of topics from pure and applied mathematics, computer science, engineering, and other related fields. While also accepting fundamental work, the journal focuses on applications. Research papers, short communications, and reviews are welcome. Technical topics within the scope include: (1) Fuzzy Information a. Fuzzy information theory and information systems b. Fuzzy clustering and classification c. Fuzzy information processing d. Hardware and software co-design e. Fuzzy computer f. Fuzzy database and data mining g. Fuzzy image processing and pattern recognition h. Fuzzy information granulation i. Knowledge acquisition and representation in fuzzy information (2) Fuzzy Sets and Systems a. Fuzzy sets b. Fuzzy analysis c. Fuzzy topology and fuzzy mapping d. Fuzzy equation e. Fuzzy programming and optimal f. Fuzzy probability and statistic g. Fuzzy logic and algebra h. General systems i. Fuzzy socioeconomic system j. Fuzzy decision support system k. Fuzzy expert system (3) Soft Computing a. Soft computing theory and foundation b. Nerve cell algorithms c. Genetic algorithms d. Fuzzy approximation algorithms e. Computing with words and Quantum computation (4) Fuzzy Engineering a. Fuzzy control b. Fuzzy system engineering c. Fuzzy knowledge engineering d. Fuzzy management engineering e. Fuzzy design f. Fuzzy industrial engineering g. Fuzzy system modeling (5) Fuzzy Operations Research [...] (6) Artificial Intelligence [...] (7) Others [...]
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