Sequential quadratic programming-based non-cooperative target distributed hybrid processing optimization method

doi:10.23919/JSEE.2023.000037

Journal of Systems Engineering and Electronics ›› 2023, Vol. 34 ›› Issue (1): 129-140.doi: 10.23919/JSEE.2023.000037

• SYSTEMS ENGINEERING • Previous Articles Next Articles

Sequential quadratic programming-based non-cooperative target distributed hybrid processing optimization method

Xiaocheng SONG¹^,*(), Jiangtao WANG²^,³(), Jun WANG²^,³(), Liang SUN²^,³(), Yanghe FENG⁴(), Zhi LI¹()

¹ Beijing Institute of Electronic Engineering, China Aerospace Science and Industry Corporation Limited, Beijing 100039, China
² School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing 100083, China
³ Institute of Artificial Intelligence, University of Science and Technology Beijing, Beijing 100083, China
⁴ School of Systems Engineering, National University of Defense Technology, Changsha 410073, China

Received:2022-10-26 Online:2023-02-18 Published:2023-03-03
Contact: Xiaocheng SONG E-mail:sxchitman@126.com;M202210564@xs.ustb.edu.cn;wangjun_ustb@163.com;liangsun@ustb.edu.cn;fengyanghe@nudt.edu.cn;lizhi1961@163.com
About author:
SONG Xiaocheng was born in 1989. He received his master degree from Harbin Institute of Technology in 2013. He is an engineer in Beijing Institute of Electronic Engineering, China Aerospace Science and Industry Corporation Limited. His research interests are air-defense and anti-missile technology, and artificial intelligence. E-mail: sxchitman@126.com

WANG Jiangtao was born in 2000. He graduated from University of Science and Technology Beijing in 2022, majoring in intelligent science and technology. He is pursuing his master degree in University of Science and Technology Beijing. His research interest is reinforcement learning-based control and optimization. E-mail: M202210564@xs.ustb.edu.cn

WANG Jun was born in 1997. He graduated from Shanxi University in 2019, majoring in automation. He received his master degree from University of Science and Technology Beijing. He is pursuing his Ph.D. degree in Beijing Institute of Technology. His research interest is spacecraft control and optimization. E-mail: wangjun_ustb@163.com

SUN Liang was born in 1986. He received his master and Ph.D. degrees from Beihang University. He is an associate professor in University of Science and Technology Beijing. His research interests are nonlinear mechanical systems control, intelligent control, and aerospace control. E-mail: liangsun@ustb.edu.cn

FENG Yanghe was born in 1985. He received his master and Ph.D. degrees from National University of Defense Technology. He is an associate professor in National University of Defense Technology. His research interests are system engineering and artificial intelligence. E-mail: fengyanghe@nudt.edu.cn

LI Zhi was born in 1961. He received his mater degree from Beihang University and Ph.D. degree from University of Electronic Science and Technology of China. He is a professor in China Aerospace Science and Industry Corporation Limited. He is an academician of Chinese Academy of Sciences. His research interests are air-defense and anti-missile technology, detection guidance and control technology. E-mail: lizhi1961@163.com
Supported by:
This work was supported by the National Natural Science Foundation of China (61903025) and the Fundamental Research Funds for the Central Universities (FRF-IDRY-20-013)

Abstract

Abstract:

The distributed hybrid processing optimization problem of non-cooperative targets is an important research direction for future networked air-defense and anti-missile firepower systems. In this paper, the air-defense anti-missile targets defense problem is abstracted as a nonconvex constrained combinatorial optimization problem with the optimization objective of maximizing the degree of contribution of the processing scheme to non-cooperative targets, and the constraints mainly consider geographical conditions and anti-missile equipment resources. The grid discretization concept is used to partition the defense area into network nodes, and the overall defense strategy scheme is described as a nonlinear programming problem to solve the minimum defense cost within the maximum defense capability of the defense system network. In the solution of the minimum defense cost problem, the processing scheme, equipment coverage capability, constraints and node cost requirements are characterized, then a nonlinear mathematical model of the non-cooperative target distributed hybrid processing optimization problem is established, and a local optimal solution based on the sequential quadratic programming algorithm is constructed, and the optimal firepower processing scheme is given by using the sequential quadratic programming method containing non-convex quadratic equations and inequality constraints. Finally, the effectiveness of the proposed method is verified by simulation examples.

Key words: non-cooperative target, distributed hybrid processing, multiple constraint, minimum defense cost, sequential quadratic programming

Xiaocheng SONG, Jiangtao WANG, Jun WANG, Liang SUN, Yanghe FENG, Zhi LI. Sequential quadratic programming-based non-cooperative target distributed hybrid processing optimization method[J]. Journal of Systems Engineering and Electronics, 2023, 34(1): 129-140.

Figures/Tables 9

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Sequential quadratic programming-based non-cooperative target distributed hybrid processing optimization method

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