Study on application of adaptive fuzzy control and neural network in the automatic leveling system

Xiping Xu, Zizhao Zhao, Wei‐Wen Lan, Lei Sha, Cheng Qian
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Abstract

This paper discusses the adaptive fuzzy control and neural network BP algorithm in large flat automatic leveling control system application. The purpose is to develop a measurement system with a flat quick leveling, Make the installation on the leveling system of measurement with tablet, to be able to achieve a level in precision measurement work quickly, improve the efficiency of the precision measurement. This paper focuses on the automatic leveling system analysis based on fuzzy controller, Use of the method of combining fuzzy controller and BP neural network, using BP algorithm improve the experience rules .Construct an adaptive fuzzy control system. Meanwhile the learning rate of the BP algorithm has also been run-rate adjusted to accelerate convergence. The simulation results show that the proposed control method can effectively improve the leveling precision of automatic leveling system and shorten the time of leveling.
自适应模糊控制和神经网络在自动调平系统中的应用研究
讨论了自适应模糊控制和神经网络BP算法在大型平地自动调平控制系统中的应用。本课题的目的是开发一种水平仪快速调平的测量系统,使水平仪安装在调平系统上,能够实现水平仪在精密测量中的快速工作,提高精密测量的效率。本文重点对基于模糊控制器的自动调平系统进行了分析,采用模糊控制器与BP神经网络相结合的方法,利用BP算法改进经验规则,构建了自适应模糊控制系统。同时对BP算法的学习率进行了运行率调整,以加快收敛速度。仿真结果表明,所提出的控制方法能有效提高自动找平系统的找平精度,缩短找平时间。
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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