| 基于CMAC神经网络的康复机器人的智能控制技术 |
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| 引用本文： | 吕广明,孙立宁,沈刚.基于CMAC神经网络的康复机器人的智能控制技术[J].哈尔滨工程大学学报,2006,27(5):662-665. |
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| 作者姓名： | 吕广明 孙立宁 沈刚 |
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| 作者单位： | 哈尔滨工业大学,机电学院,黑龙江,哈尔滨,150001 |
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| 基金项目： | 国家高技术研究发展计划(863计划) |
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| 摘 要： | 康复机器人是目前的热点方向之一.建立了五自由度上肢康复机器人的CMAC神经网络控制模型.在此模型基础上,通过对正常人肌电信号的训练学习,修正了网络的权值,得到了较为理想的控制模型.最后,通过病人的肌电信号,得到了良好的输出结果.仿真实例表明,CMAC方法比其他神经网络方法收敛快,学习精度高,且具有更好的网络泛化能力,可以用于五自由度上肢康复机器人的智能控制.
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| 关 键 词： | 康复机器人 肌电信号 CMAC神经网络 网络泛化能力 CMAC仿真实例 |
| 文章编号： | 1006-7043(2006)05-0662-04 |
| 修稿时间： | 2005年6月27日 |
Intellectual control technology of rehabilitant robot based on CMAC neural network |
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| L Guang-ming,SUN Li-ning,SHEN Gang.Intellectual control technology of rehabilitant robot based on CMAC neural network[J].Journal of Harbin Engineering University,2006,27(5):662-665. |
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| Authors: | L Guang-ming SUN Li-ning SHEN Gang |
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| Affiliation: | L(U) Guang-ming,SUN Li-ning,SHEN Gang |
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| Abstract: | A computer automated measurement and control(CAMC) network model was built for a 5 degrees of freedom(DOF) upper limb rehabilitant robot.The weight of the network was adjusted for the electromyography(EMG) signal of ordinary people and the control model of a more ideal was obtained.At last,the well output effect was achieved by the EMG signal of patients.Simulations showed that the learning accuracy of the CMAC method was higher and converged fast than conventional means and the capacity of network generalization was better.Thus,the method can be used for the intellectual control of a 5-DOF upper limb rehabilitant robot. |
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| Keywords: | rehabilitant robot electromyography(EMG) signal computer automated measurement and control(CMAC) neural network capacity of network generalization CMAC simulations |
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