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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Main Authors: Qiang Zhao, Qizhong Tang, Junli Han, Ming Yang, Zhihua Chen
Format: Article
Language:English
Published: Hindawi Limited 2019-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2019/7689860
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spelling 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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