控制理论(社会学)
计算机科学
路径(计算)
理论(学习稳定性)
跟踪(教育)
量化(信号处理)
算法
模糊逻辑
数学优化
数学
人工智能
控制(管理)
机器学习
心理学
教育学
程序设计语言
作者
Dequan Zhu,M. Shi,Li Wang,Kang Xue,Juan Liao,Wei Xiong,Fuming Kuang,Shun Zhang
出处
期刊:Robotica
[Cambridge University Press]
日期:2023-07-10
卷期号:41 (10): 3116-3136
被引量:3
标识
DOI:10.1017/s0263574723000905
摘要
Abstract During the operation of automatic navigation rice transplanter, the accuracy of path tracking is influenced by whether the transplanter can enter the stable state of linear path tracking quickly, thus affecting the operation quality and efficiency. To reduce the time to enter the path tracking stable state and improve the tracking accuracy and stability for the rice transplanter, path tracking control method based on variable universe fuzzy control (VUFC) and improved beetle antenna search (BAS) is proposed in this paper. VUFC is applied to achieve adaptive adjustment of the fuzzy universe by dynamically adjusting the quantization and scaling factors according to the variations of errors by the contraction–expansion factor. To solve the problem of setting the contraction–expansion factor in VUFC and real-time performance, an offline parameter optimization method is presented to calculate the optimal contraction–expansion factor by an iterative optimization algorithm in a path tracking simulation model, where the iterative optimization algorithm is the BAS algorithm improved by the isolated niching technique and adaptive step size strategy in this paper. To verify the effectiveness of the proposed path tracking control method, simulation and field linear path tracking experiments were carried out. Experimental results indicate that the proposed method reduces the time of entering the stable state of linear path tracking and improves the accuracy and stability of path tracking compared with the pure pursuit control method.
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