| 基于Volterra 级数对火工品起爆过程的辨识 |
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| 引用本文： | 徐文文.基于Volterra 级数对火工品起爆过程的辨识[J].兵工自动化,2019,38(8). |
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| 作者姓名： | 徐文文 |
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| 作者单位： | 西安工业大学电子信息工程学院，西安 710021 |
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| 基金项目： | 陕西省教育厅专项科研计划项目(17JK1069) |
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| 摘 要： | 为解决火工品起爆过程中线性函数不能解决元件参数变化、不确定性和非线性强的问题，将Volterra 级
数模型与基因表达式编程(gene expression programing，GEP)相结合，设计一种新的火工品起爆过程辨识算法。利用
Volterra 级数能准确反应非线性系统的特征来描述火工品起爆过程，GEP 算法则克服传统辨识方法的不足，辨识出正
确的模型。仿真结果表明，该方法能精确、快速地辨识出火工品起爆过程。
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| 关 键 词： | 火工品 非线性 Volterra 级数 基因表达式编程GEP 算法 |
| 收稿时间： | 2019/4/4 0:00:00 |
| 修稿时间： | 2019/5/14 0:00:00 |
Identification of Initiation Process of Initiating Explosive Based on Volterra Series |
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| Abstract: | In order to solve the problem that the linear function can not solve the variation, uncertainty, and strong
nonlinearity of component parameters in initiation process of initiating explosive device, a new identification algorithm for
initiation process of initiating explosive device is designed by combining Volterra series model with gene expression
programming. Volterra series can accurately reflect the characteristics of non-linear system to describe the initiation
process of initiating explosive devices. GEP algorithm overcomes the shortcomings of traditional identification methods
and identifies the correct model. The simulation results show that the method can accurately and quickly identify initiating
process of initiating explosive device. |
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| Keywords: | initiating explosive nonlinear Voltrerra series gene expression programming algorithm |
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