基于CMAC在线学习的电动轮椅姿态控制

S. Fujisawa, K. Akazawa, R. Kurozumi, K. Kawada, T. Yamamoto, H. Uenaka
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引用次数: 0

摘要

采用CMAC神经网络控制方法,开发了一种电动轮椅主动悬架姿态控制系统。利用小脑模型算法控制器(CMAC)的学习功能,将学习结果作为在线输入目标值的输出,对轮椅的姿态控制进行了测试。本文通过仿真和系统实验对保持姿态水平的学习控制进行了测试,并与常规方法进行了比较,验证了CMAC方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Posture control by on-line learning using CMAC for electric wheelchairs
We developed a posture control system for an electric wheelchair equipped with active suspension, using CMAC, which is a neural network type of control. Testing of the posture control of the wheelchair, which considers a learning results as an output to the target value inputted on-line using the learning function of CMAC (cerebellar model arithmetic controller), was performed. In this paper, testing of the learning control, which holds the posture horizontally both by the simulation and in the experiment by the system, is performed, and the validity of CMAC is verified compared with conventional method.
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