| 某扫雷犁电液伺服系统的模糊神经网络控制 |
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| 引用本文： | 王力,彭湧,王永超. 某扫雷犁电液伺服系统的模糊神经网络控制[J]. 火力与指挥控制, 2012, 37(4): 101-104,108 |
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| 作者姓名： | 王力 彭湧 王永超 |
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| 作者单位： | 1. 南京理工大学机械工程学院,南京,210094
2. 北方自动控制技术研究所,太原,030006 |
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| 摘 要： | 针对某扫雷犁电液伺服系统这一典型的非线性系统,使用基于减法聚类的模糊神经网络(FNN)自学习算法设计了控制器,其中减法聚类用于确定模糊神经网络的初始结构。在网络的学习过程中,对结论参数采用最小二乘法进行辨识,对前提参数采用误差反传算法进行调整;并使用AMESim软件搭建了扫雷犁的液压系统模型,利用其接口技术实现了与Simulink的联合仿真。实验结果表明模糊神经网络控制器的控制效果要优于传统的PID控制器。
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| 关 键 词： | 扫雷犁 减法聚类 模糊神经网络 联合仿真 |
Control of the Electrohydraulic System of a Certain Mine Sweeping Plough Based on Fuzzy Neural Network |
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| WANG Li , PENG Yong , WANG Yong-chao. Control of the Electrohydraulic System of a Certain Mine Sweeping Plough Based on Fuzzy Neural Network[J]. Fire Control & Command Control, 2012, 37(4): 101-104,108 |
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| Authors: | WANG Li PENG Yong WANG Yong-chao |
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| Affiliation: | 1 (1.School of Mechanical Engineering,Nanjing University of Science and Technology,Nanjing 210094,China, 2.North Automatic Control Technology Institute,Taiyuan 030006,China) |
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| Abstract: | A self-learning algorithm of fuzzy neural network based on subtractive clustering was presented for control of the electrohydraulic system of a certain mine sweeping plough with typical nonlinear characteristic.Subtractive clustering algorithm was used to determine the initial structure of fuzzy neural network.In the process of learning of network,the result parameter was identified by least square method and the premise parameter was identified by back-propagation algorithm.The model of mine sweeping plough was established in AMESim,and co-simulation was achieved with the interface between AMESim and Simulink.The simulation results show that the fuzzy controller is better than PID controller. |
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| Keywords: | mine sweeping plough subtractive clustering fuzzy neural network co-simulation |
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