基于模糊熵加权融合的单轨运输机器人动态倾角辨识研究

doi:10.3969/j.issn.1000-1158.2024.07.03

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Abstract For the problem of low identification accuracy in detecting the dynamic inclination angle of monorail robots, a precise identification method for the dynamic inclination angle of monorail transport robot based on fuzzy entropy weighted fusion is proposed. Firstly, based on the constructed dual model of orbit curvature and inclination angle change, the improved forgetting recursive least squares (IFFRLS) algorithm is used to calculate the dynamic change rate of orbit curvature and inclination angle respectively. Secondly, taking the orbit curvature value and the dynamic change rate of inclination angle as input values, the extended Kalman filter (EKF) and unscented Kalman filter (UKF) algorithms are used to iteratively update and calculate the dynamic angle of inclination angle respectively. Finally, the global fuzzy entropy weighted fusion (GFEWF) is used to deeply fuse the angle values to improve the detection accuracy of dynamic inclination angle. The experiments show that the global fuzzy entropy weighted fusion (GFEWF) algorithm based on double model improves the identified dynamic inclination accuracies in rail segment 1 and rail segment 2 by 10.38% and 25.60% on average, respectively, compared with the single model-based UKF or EKF algorithms.

Key words： geometric measurement monorail transport robot dynamic inclination angle;recursive least squares algorithm unscented Kalman filter global fuzzy entropy

Received: 28 August 2023 Published: 04 July 2024

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TB922

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	Articles by authors
	LIU Zechao
	LI Jingzhao
	ZHENG Changlu
	WANG Guofeng

Cite this article:

LIU Zechao,LI Jingzhao,ZHENG Changlu, et al. Research on Dynamic Inclination Angle Identification of Monorail Transportation Robot Based on Fuzzy Entropy Weighted Fusion[J]. Acta Metrologica Sinica, 2024, 45(7): 941-951.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2024.07.03 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2024/V45/I7/941

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