Efficient Method of Firing Angle Calculation for Multiple Launch Rocket System Based on Polynomial Response Surface and Kriging Metamodels
Aiming at solving the problem of firing angle calculation for the multiple launch rocket system (MLRS) under both standard and actual atmospheric conditions, an efficient method based on large sample data and metamodel is proposed. The polynomial response surface, Kriging, and the ensemble of metamo...
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Series: | Mathematical Problems in Engineering |
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doaj-142eb5c27eb548b383319999fc1785bb2020-11-25T00:33:25ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472019-01-01201910.1155/2019/76898607689860Efficient Method of Firing Angle Calculation for Multiple Launch Rocket System Based on Polynomial Response Surface and Kriging MetamodelsQiang Zhao0Qizhong Tang1Junli Han2Ming Yang3Zhihua Chen4Key Laboratory of Transient Physics, Nanjing University of Science and Technology, Nanjing 210094, ChinaNavigation and Control Technology Institute, China North Industries Croup Corporation, Beijing 100089, ChinaBeijing Institute of Electromechanical Technology, Beijing 100083, ChinaNavigation and Control Technology Institute, China North Industries Croup Corporation, Beijing 100089, ChinaKey Laboratory of Transient Physics, Nanjing University of Science and Technology, Nanjing 210094, ChinaAiming at solving the problem of firing angle calculation for the multiple launch rocket system (MLRS) under both standard and actual atmospheric conditions, an efficient method based on large sample data and metamodel is proposed. The polynomial response surface, Kriging, and the ensemble of metamodels are used to establish the functional relations between the firing angle, the maximum range angle, the maximum range, and various influencing factors under standard atmospheric conditions, and related processes are described in detail. On this basis, the initial values for the first two iterations are determined with the meteorological data being made full use of in the six degrees of freedom trajectory simulation, and then the firing angle corresponding to a specific range is automatically and iteratively calculated. The efficient method of firing angle calculation for the typical MLRS has been extensively tested with three cases. The results show that the high-order polynomial response surface, the Kriging predictors with Cubic, Gauss, and Spline correlation functions, and the ensemble of above four individual metamodels have better performances for predicting the firing angle under standard atmospheric conditions compared with those of other metamodels under identical conditions, and execution times of the above four individual metamodels with a training sample size of 9000 are all less than 0.9ms, which verifies the effectiveness and feasibility of the proposed method for calculating the firing angle under standard atmospheric conditions. Moreover, the number of iterations is effectively reduced by using the proposed iterative search approach under actual atmospheric conditions. This research can provide guidance for designing the fire control and command control system of the MLRS.http://dx.doi.org/10.1155/2019/7689860 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Qiang Zhao Qizhong Tang Junli Han Ming Yang Zhihua Chen |
spellingShingle |
Qiang Zhao Qizhong Tang Junli Han Ming Yang Zhihua Chen Efficient Method of Firing Angle Calculation for Multiple Launch Rocket System Based on Polynomial Response Surface and Kriging Metamodels Mathematical Problems in Engineering |
author_facet |
Qiang Zhao Qizhong Tang Junli Han Ming Yang Zhihua Chen |
author_sort |
Qiang Zhao |
title |
Efficient Method of Firing Angle Calculation for Multiple Launch Rocket System Based on Polynomial Response Surface and Kriging Metamodels |
title_short |
Efficient Method of Firing Angle Calculation for Multiple Launch Rocket System Based on Polynomial Response Surface and Kriging Metamodels |
title_full |
Efficient Method of Firing Angle Calculation for Multiple Launch Rocket System Based on Polynomial Response Surface and Kriging Metamodels |
title_fullStr |
Efficient Method of Firing Angle Calculation for Multiple Launch Rocket System Based on Polynomial Response Surface and Kriging Metamodels |
title_full_unstemmed |
Efficient Method of Firing Angle Calculation for Multiple Launch Rocket System Based on Polynomial Response Surface and Kriging Metamodels |
title_sort |
efficient method of firing angle calculation for multiple launch rocket system based on polynomial response surface and kriging metamodels |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2019-01-01 |
description |
Aiming at solving the problem of firing angle calculation for the multiple launch rocket system (MLRS) under both standard and actual atmospheric conditions, an efficient method based on large sample data and metamodel is proposed. The polynomial response surface, Kriging, and the ensemble of metamodels are used to establish the functional relations between the firing angle, the maximum range angle, the maximum range, and various influencing factors under standard atmospheric conditions, and related processes are described in detail. On this basis, the initial values for the first two iterations are determined with the meteorological data being made full use of in the six degrees of freedom trajectory simulation, and then the firing angle corresponding to a specific range is automatically and iteratively calculated. The efficient method of firing angle calculation for the typical MLRS has been extensively tested with three cases. The results show that the high-order polynomial response surface, the Kriging predictors with Cubic, Gauss, and Spline correlation functions, and the ensemble of above four individual metamodels have better performances for predicting the firing angle under standard atmospheric conditions compared with those of other metamodels under identical conditions, and execution times of the above four individual metamodels with a training sample size of 9000 are all less than 0.9ms, which verifies the effectiveness and feasibility of the proposed method for calculating the firing angle under standard atmospheric conditions. Moreover, the number of iterations is effectively reduced by using the proposed iterative search approach under actual atmospheric conditions. This research can provide guidance for designing the fire control and command control system of the MLRS. |
url |
http://dx.doi.org/10.1155/2019/7689860 |
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