The estimation of the type and parameter of flow field is important for robotic fish.Recent estimation methods cannot meet the requirements of the robotic fish due to the lack of prior knowledge or the under-fitting of the model.A processing method including data preprocessing,feature extraction,feature selection,flow type classification and flow field parameters estima-tion,is proposed based on the data of the pressure sensors in an artificial lateral line.Probabilistic Neural Network(PNN)is used to classify the flow field type and the Generalized Regressive Neural Network(GRNN)is the best choice for estimating the flow field parameters.Also,a few filtering methods for data preprocessing,three methods for feature selection and nine parameters estimation methods are analysis for choosing better method.The proposed method is verified by the experiments with both simulation and real data.

Bing Sun;Yi Xu;Shuhang Xie;Dong Xu;Yupu Liang

School of Electronics and Information Engineering,Beihang University,Beijing 100191,Beijing,China;School of Automation Science and Electrical Engineering,Beihang University,Beijing 100191,Beijing,China

仿生工程学报（英文版）

[1]Bing Sun;Yi Xu;Shuhang Xie;Dong Xu;Yupu Liang-.Data Processing Methods of Flow Field Based on Artificial Lateral Line Pressure Sensors)[J].仿生工程学报（英文版）,2022(06):1797-1815

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