基于模糊c回归模型的BELS方法用于非线性系统辨识

2013 International Conference on Electrical Engineering and Software Applications Pub Date : 2013-03-21 DOI:10.1109/ICEESA.2013.6578425

B. Aissaoui, M. Soltani, D. Elleuch, A. Chaari

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引用次数: 0

摘要

提出了一种基于消偏最小二乘法的模糊c回归模型聚类算法。该方法的目的是建立一个有噪声非线性系统的辨识程序。使用BELS方法识别后续参数并消除偏差。将该方法应用于基准建模问题，取得了良好的效果。

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Fuzzy c-regression models based on the BELS method for nonlinear system identification

A fuzzy c-regression model clustering algorithm based on Bias-Eliminated Least Squares method (BELS) is presented. This method is designed to develop an identification procedure for noisy nonlinear systems. The BELS method is used to identify consequent parameters and eliminate the bias. The proposed approach has been applied to benchmark modeling problem which proved a good performance.

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2013 International Conference on Electrical Engineering and Software Applications

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