Two Identification Methods for a Nonlinear Membership Function. (3rd May 2021)

• Record Type: Journal Article
• Authors: Ji, Yuejiang; Lv, Lixin
• Other Names: Zhu Quanmin Academic Editor.
• Is Part Of: Complexity. Volume 2021(2021)
• Publication Date: 2021-05-03
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2021/5515888
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : This paper proposes two parameter identification methods for a nonlinear membership function. An equation converted method is introduced to turn the nonlinear function into a concise model. Then a stochastic gradient algorithm and a gradient-based iterative algorithm are provided to estimate the unknown parameters of the nonlinear function. The numerical example shows that the proposed algorithms are effective.