| 基于神经网络的非线性控制系统自组织辨识 |
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| 引用本文： | 胡德文,王正志,周宗潭.基于神经网络的非线性控制系统自组织辨识[J].国防科技大学学报,1998,20(2):85-90. |
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| 作者姓名： | 胡德文 王正志 周宗潭 |
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| 作者单位： | 国防科技大学自动控制系 |
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| 基金项目： | 国家自然科学基金,湖南省自然科学基金 |
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| 摘 要： | 本文首先将自组织神经网络算法向一般化情形引伸，接着把自组织过程应用到一般非线性系统的动态过程分类，使得整个非线性系统能够按照输入输出样本空间的概率密度自组织，成为许多具有不同分类核心和感受野的线性子空间逼近。在此基础上，我们采用通用最小二乘算法，以子空间的非线性问题线性化误差作为依据，并进一步运用自组织神经网络的合作与竞争思想，最终得到一般情形的非线性系统的最小二乘辨识。仿真结果表明了本方法的可行性与优越性。
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| 关 键 词： | 非线性系统，神经网络，最小二乘算法，自组织算法，系统辨识 |
| 收稿时间： | 1998/2/18 0:00:00 |
Self-organizing Identification of Nonlinear Control Systems Based on Neural Networks |
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| Hu Dewen,Wang Zhengzhi and Zhou Zhongtan.Self-organizing Identification of Nonlinear Control Systems Based on Neural Networks[J].Journal of National University of Defense Technology,1998,20(2):85-90. |
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| Authors: | Hu Dewen Wang Zhengzhi and Zhou Zhongtan |
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| Affiliation: | Department of Automatic Control, NUDT, Changsha, 410073;Department of Automatic Control, NUDT, Changsha, 410073;Department of Automatic Control, NUDT, Changsha, 410073 |
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| Abstract: | This paper firstly extends the self organizing neural networks to general case.Then the self organizing process is applied to classify the dynamic process of nonlinear control systems.The nonlinear system is self organized according to the probability density of the input and output samples and is approximated by many linear sub spaces with different classifying centers and receptive fields.The self organizing least squares identification of nonlinear systems is constructed based on the general least squares algorithms,the linearization errors of sub spaces,and the cooperation and competition mechanism.The simulation results have shown the efficiency of the suggested algorithm. |
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| Keywords: | Nonlinear systems neural networks least squares algorithm self organizing system identification |
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