摘要
模糊系统的一致逼近能力和可解释性能使得其能够直观高效地描述复杂的非线性不确定系统。然而,复杂系统的模糊建模方法面临"规则爆炸"的挑战。该文首先回顾了模糊系统一致逼近性以及模糊系统逼近的充分条件和必要条件。在此基础上,综述了基于数据驱动的模糊系统辨识方法,并重点介绍了流行的稀疏表达思想在模糊系统辨识领域中的应用。
The uniform approximation and interpretability of fuzzy system make it possible to describe complex nonlinear uncertain systems intuitively and efficiently.However, fuzzy modeling approach of complex systems faces the challenge of ＂rule explosion＂.In this paper, we firstly reviewed the uniform approximations of fuzzy systems and the sufficient and necessary conditions of approximation property of fuzzy systems.On this basis, we summarizes identification approaches of fuzzy systems based on data driven, and focus onsparse representationin the application of fuzzy system identification.
关键词
模糊系统
一致逼近
数据驱动模糊建模
Fuzzy Systems
Uniform Approximation
Data-driven Fuzzy Modeling
