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Application of fuzzy sets theory in process data filtering

机译:模糊集理论在过程数据过滤中的应用

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Fuzzy sets theory is introduced and applied to the problems of signal restoration. A fuzzy approach for system identification and state estimation is developed. The estimated values obtained from the fuzzy model are in the form of fuzzy numbers which present the possibility of the system structure. Both L-R and symmetric triangular type membership functions are employed to derive the fuzzy-data based estimator (FBE). Illustrative examples with white and color noise are provided to demonstrate the applicability and effectiveness of the developed FBE. Comparisons between the FBE and various modified Kalman filter are also included.
机译:介绍了模糊集理论并将其应用于信号恢复问题。提出了一种用于系统辨识和状态估计的模糊方法。从模糊模型获得的估计值采用模糊数的形式,这代表了系统结构的可能性。 L-R和对称三角型隶属度函数均用于导出基于模糊数据的估计器(FBE)。提供了具有白色和彩色噪声的说明性示例,以证明已开发的FBE的适用性和有效性。 FBE和各种改进的卡尔曼滤波器之间的比较也包括在内。

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