| 非线性随机动态系统学习建模方法 |
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| 引用本文： | 覃祖旭 张洪钺. 非线性随机动态系统学习建模方法[J]. 北京航空航天大学学报, 1996, 22(6): 682-686 |
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| 作者姓名： | 覃祖旭 张洪钺 |
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| 作者单位： | 北京航空航天大学自动控制系 |
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| 摘 要： | 在动态神经网络及扩展卡尔曼滤波算法的基础上，提出了对非线性随机动态系统进行学习建模的迭代算法，用这种方法对非线性随机系统建模，可以获得更准确伯系统模型，并可对非线性随机系统进行状态估计。最后给出相应算法及仿真结果。
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| 关 键 词： | 神经网络 非线性系统 卡尔曼滤波 |
LEARNING METHOD FOR NONLINEAR STOCHATICS DYNAMIC SYSTEM MODELING |
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| Qin Zuxu Zhang Hongyue. LEARNING METHOD FOR NONLINEAR STOCHATICS DYNAMIC SYSTEM MODELING[J]. Journal of Beijing University of Aeronautics and Astronautics, 1996, 22(6): 682-686 |
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| Authors: | Qin Zuxu Zhang Hongyue |
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| Abstract: | A modeling method for nonlinear stochastics dynamic system(NSDS) based on neural network and extended Kalman filter(EKF) is presented. Using this method, the contaminated data by noise can be filtered by EKF. A dynamic neural network(DNN) which is a good approximation to the deterministic part of the NSDS can be obtained. Meanwhile the DNN can be used as a state estimator for the NSDS. In the end of the paper a simulation is shown. |
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| Keywords: | neural networks non linear systems Kalman filtering |
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