Dynamic fuzzy neural network algorithm based on EKF and TLS

ZHANG Caixia

doi:10.13471/j.cnki.acta.snus.2019.01.017

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Dynamic fuzzy neural network algorithm based on EKF and TLS

更新时间：2023-12-11

- Dynamic fuzzy neural network algorithm based on EKF and TLS
- Acta Scientiarum Naturalium Universitatis SunYatseni Vol. 58, Issue 1, Pages: 138-143(2019)
- 作者机构：
  
  佛山科学技术学院自动化学院,广东,佛山,528000
- 作者简介：
- 基金信息：
- DOI：10.13471/j.cnki.acta.snus.2019.01.017
  CLC：
- Published：2019，
  
  Published Online：25 January 2019，
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ZHANG Caixia. Dynamic fuzzy neural network algorithm based on EKF and TLS. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 58(1):138-143(2019)
DOI：

ZHANG Caixia. Dynamic fuzzy neural network algorithm based on EKF and TLS. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 58(1):138-143(2019) DOI： 10.13471/j.cnki.acta.snus.2019.01.017.

摘要

提出了一种动态模糊神经网络（D-FNN）算法。在实际应用中，可以用卡尔曼滤波（KF）方法来调节D-FNN结果参数，同时，EKF（扩展卡尔曼滤波）方法用于更新前提参数的中心和宽度，从而使得所有参数都被修正。该算法可用于平滑、滤波或者预测非线性动态系统的状态，同其他基于梯度的在线算法相比，EKF可以加快D-FNN收敛速度。采用总体最小二乘（TLS）方法作为修剪技术来选择D-FNN重要的模糊规则。如果在学习进行时，检测到不活跃的模糊规则并加以剔除，则可获得更为紧凑的DFNN结构， TLS方法是用来补偿线性参数估计问题中数据误差的一种技术。最后针对实际案例进行了仿真分析，验证了该算法的有效性和高效性。

Abstract

A dynamic fuzzy neural network algorithm (D-FNN) is proposed. In practical application

Kalman filter (KF) is used to adjust the result parameters of D-FNN. Meanwhile

extended Kalman filter (EKF) is used to update the center and width of the premise parameters

so that all parameters can be modified. This algorithm is used to smooth

filter or predict the state of a nonlinear dynamic system. Comparing to other online algorithms which are based on gradient

EKF can accelerate the convergence speed of D-FNN. The total least squares (TLS) is a pruning technique to select the important fuzzy rules of D-FNN

which also is a technique to compensate data error in linear parameter estimation problem. If the inactive fuzzy rules are detected and removed during the learning process

a more compact D-FNN structure can be obtained. Finally

a simulation analysis for actual case verify the effectiveness and efficiency of the algorithm.

关键词

动态模糊神经网络修剪技术模糊规则径向基神经网络

Keywords

D-FNNpruning techniquefuzzy rulesRBF neural network

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Related Institution

Department of Computer Science,Foshan University

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Department of Electrical Engineering, Harbin Institute of Technology

School of Electronic and Information Engineering, Foshan University

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