| 引用本文: | 黄敏超,张育林,陈启智.共轭梯度反传算法及其在液体火箭发动机系统辨识中的应用.[J].国防科技大学学报,1995,17(2):27-32.[点击复制] |
| Huang Minchao,Zhang Yulin,Chen Qizhi.Conjugate Gradient Back-propagation Algorithm and Its Application on System Identification of Liquid Rocket Engine[J].Journal of National University of Defense Technology,1995,17(2):27-32[点击复制] |
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| 共轭梯度反传算法及其在液体火箭发动机系统辨识中的应用 |
| 黄敏超, 张育林, 陈启智 |
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(国防科技大学 航天技术系 湖南 长沙 410073)
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| 摘要: |
| 结合非线性优化理论和方法提出了易于实现、收敛速度比较快的多层神经网络共轭梯度反传算法。液体火箭发动机参数辨识技术已得到广泛的应用，由于传统的数学方法必须基于发动机已知模型，使得其参数辨识受到极大的限制。文中基于神经网络共轭梯度反传算法进行液体火箭发动机的系统辨识，结合变推力发动机热试车动态数据，得到了满意的仿真结果。 |
| 关键词: 液体火箭发动机 神经网络 共轭梯度反传算法 系统辨识 |
| DOI： |
| 投稿日期：1994-03-21 |
| 基金项目:国家自然科学基金资助项目 |
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| Conjugate Gradient Back-propagation Algorithm and Its Application on System Identification of Liquid Rocket Engine |
| Huang Minchao, Zhang Yulin, Chen Qizhi |
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(Department of Aerospace Technology)
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| Abstract: |
| A conjugate gradient back-propagation (CGBP) algorithm of a multilayered neural network is presented with the theory and methods for nonlinear optimization. Since this learning algorithm needn't compute the second derivative，it is worked out easily. Furthermore，the CGBP belongs to the superlinear convergence algorithm so that the performance of the multilayered neural network is improved in comparison with the general back-propagation algorithm. The identification techniques have been widely applied to the field of the liquid rocket engine (LRE). Because the engine model must have been known before the system identified with traditional mathematical method，the identification method of parameter is extremely restrained in the engine. Based on the neural network conjugate gradient algorithm，the experimental data of a variable thrust rocket engine is presented to the neural network，and a satisfied identification model is obtained in this paper. |
| Keywords: liquid rocket engine neural network conjugate gradient back-propagarion algorithm system identification |
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