基于改进粒子群优化极限学习机的弹丸参数辨识

doi:10.12305/j.issn.1001-506X.2023.02.24

Abstract

Abstract:

In view of the identification results diverge when using extreme learning machine to identify the aerodynamic parameters of the projectile, due to the randomly generated input weights and hidden layer neuron thresholds, an adaptive mutation particle swarm optimization extreme learning machine algorithm is proposed. The paper introduces the adaptive update strategy and particle mutation strategy into particle swarm optimization algorithm and couples it with extreme learning machine. The proposed algorithm optimizes the input weights and hidden layer thresholds of extreme learning machine through adaptive mutation particle swarm optimization algorithm, the adaptive update strategy and particle mutation strategy in algorithm effectively improve the performance of the algorithm. Simulation experiments show that the use of adaptive mutation particle swarm optimization extreme learning machine exceedingly improve identification accuracy and convergence speed, which is practical in engineer application.

Key words: projectile, aerodynamic parameter identification, extreme learning machine, particle swarm optimization algorithm, adaptive update strategy, particle mutation strategy

CLC Number:

TJ412

Youran XIA, Jun GUAN, Wenjun YI. Projectile parameter identification: extreme learning machine optimized by improved particle swarm[J]. Systems Engineering and Electronics, 2023, 45(2): 521-529.

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参数	设定值
最大迭代次数	1 000
最大速度	0.3
最小速度	-0.3
最大速度惯性权重	0.8
最小速度惯性权重	0.2
个体认识系数	1.596 18
社会认知系数	1.832 45
方差判别阈值	0.03
变异概率	0.01

测试函数	算法	粒子数	最大值	最小值	平均值	平均收敛迭代次数	理论值
Sphere	PSO	50	0.515	0.336	0.130	676	0
		100	0.050	0.004	0.018	489	0
		150	0.006	0.001	0.002	396	0
	AMPSO	50	4.17×10^－37	2.89×10^－52	7.64×10^－40	441	0
		100	6.91×10^－42	8.52×10^－54	1.54×10^－46	313	0
		150	9.15×10^－47	2.61×10^－58	1.17×10^－51	245	0
Schaffer	PSO	50	0.037	0.008	0.011	718	0
		100	0.037	0.009	0.010	502	0
		150	0.009	1.98×10^－17	0.008	429	0
	AMPSO	50	0.009	0	6.55×10^－4	489	0
		100	0.009	0	8.27×10^－5	298	0
		150	0.000	0	0	264	0

参数	数值
初速/(m/s)	930
射角/(°)	45
射向/(°)	95.595
自转角速度/(rad/s)	188.5

算法	结构	辨识精度	辨识时间/s
ELM	5-70-7	3.34×10^－5	7.68
PSO-ELM	5-65-7	5.41×10^－10	18.23
AMPSO-ELM	5-45-7	7.17×10^－12	8.02

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Projectile parameter identification: extreme learning machine optimized by improved particle swarm

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