随机环境下非线性系统辨识的鲁棒区间2型FCRM算法

2017 International Conference on Control, Automation and Diagnosis (ICCAD) Pub Date : 1900-01-01 DOI:10.1109/CADIAG.2017.8075653

Khadhraoui Sameh, A. Chaari

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引用次数: 0

摘要

本文研究了区间2型模糊c回归算法对噪声和离群值的敏感性。为了克服这一问题，本文提出了该算法的改进版本。采用加权递推最小二乘法估计局部模型的结果参数。使用两个示例对该方法进行了测试和验证。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Robust interval type-2 FCRM algorithm for nonlinear systems identification in a stochastic environment

This paper investigates the sensibility of the interval type-2 fuzzy c-regression algorithm to noise and outliers. To overcome this problem, a modified version of this algorithm is presented. The consequences parameters of local models are estimated using the weighted recursive least squares method. This approach is tested and validated using two examples.

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2017 International Conference on Control, Automation and Diagnosis (ICCAD)

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