A Survey on Zeroing Neural Networks Aided by Fuzzy System
Chengfu Yi, Jie Chen, Zhi Xie, Yuhuan Chen · Computational Intelligence · 2026
ABSTRACT Zeroing neural networks are widely applied in engineering fields. However, in practical scenarios, the problems they face often exhibit characteristics of uncertainty and fuzziness, and zeroing neural networks have obvious deficiencies in handling such uncertain problems. To address these deficiencies, researchers have combined zeroing neural networks with fuzzy systems. By leveraging the inherent advantages of fuzzy systems in dealing with uncertainty and fuzziness, this integration provides an effective way to expand the application scenarios of zeroing neural networks. This paper reviews the fusion and practical applications of two types of fuzzy systems (namely the Mamdani fuzzy system and the Takagi‐Sugeno fuzzy system) with zeroing neural networks, aiming to offer references for subsequent research in this direction.