| 基于GRNN 的机器鱼直游稳态速度建模 |
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| 引用本文： | 郭顺利,朱其新,谢广明. 基于GRNN 的机器鱼直游稳态速度建模[J]. 兵工自动化, 2010, 29(11): 82-84. DOI: 10.3969/j.issn.1006-1576.2010.11.024 |
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| 作者姓名： | 郭顺利 朱其新 谢广明 |
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| 作者单位： | 华东交通大学电气与电子学院,江西,南昌,330013;北京大学工学院,北京,100871 |
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| 基金项目： | 国家自然科学基金资助(10972003) |
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| 摘 要： | 为解决机器鱼动力学建模中瞬变的强非线性流动控制等难点问题,建立基于广义回归神经网络（General Regression Neural Network,GRNN）的机器鱼直游稳态速度模型。以三关节仿生机器鱼为研究对象,利用神经网络的非线性逼近能力,使用GRNN辨识机器鱼游速与其运动参数之间的强非线性关系,建立了电机控制参数与仿生机器鱼直游稳态速度之间关系的模型,并通过实验进行了预测值与实际值之间的误差分析。实验结果证明,采用GRNN神经网络辨识技术建立仿科机器鱼直游速度模型是完全可行的。
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| 关 键 词： | 仿生机器鱼 运动参数 GRNN神经网络 直游速度模型 |
| 收稿时间： | 2013-01-08 |
Steady-State Velocity Modeling of Robot Fish Swimming Straight Based on GRNN |
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| Guo Shunli,Zhu Qixin,Xie Guangming. Steady-State Velocity Modeling of Robot Fish Swimming Straight Based on GRNN[J]. Ordnance Industry Automation, 2010, 29(11): 82-84. DOI: 10.3969/j.issn.1006-1576.2010.11.024 |
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| Authors: | Guo Shunli Zhu Qixin Xie Guangming |
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| Affiliation: | Guo Shunli1,Zhu Qixin1,Xie Guangming2(1.College of Electrical & Electronic,ECJT University,Nanchang 330013,China,2.College of Engineering,Peking University,Beijing 100871,China) |
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| Abstract: | To resolve the difficult problems in robot fish dynamics modeling such as transient strongly nonlinear flow control,establish the robot fish straight swim steady-state velocity model based on general regression neural network(GRNN).Taking the three joints biomimetic robot fish as the researching object,use the nonlinear approximation capability of the neural networks,make use of GRNN to recognize the strongly nonlinear relationship between robot fish swim velocity and its motional parameters,set up the rela... |
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| Keywords: | biomimetic robot fish motion parameters GRNN neural network straight swim velocity model |
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