基于置信规则库的捷联惯组误差系数预测方法

doi:10.3969/j.issn.1001-506X.2020.12.24

摘要/Abstract

摘要：

捷联惯组(strapdown inertial measurement unit, SIMU)是火箭等大型飞行器控制系统的核心部件,结构复杂，可获得的误差系数样本较为缺乏。置信规则库(belief rule base, BRB)作为一种专家系统能够有效融合专家知识和监测数据,可以有效处理小样本情况下复杂系统建模问题。鉴于此,本文提出了一种基于BRB的SIMU误差系数预测方法。为充分利用脉冲量输入信息,提高信息转换精度,降低指标转换过程中的信息损失,根据惯组脉冲量输出特点提出了一种新的匹配度计算方法,提升模型的精度。最后,以某型SIMU加速度计为例验证了所提方法的有效性。

关键词: 捷联惯组, 误差系数, 置信规则库, 专家知识, 匹配度

Abstract:

The strapdown inertial measurement unit (SIMU) is the core of such large aircraft control systems as the rocket. Its structure is quite complicated, and the available error parameter samples are relatively few. As a kind of expert system, the belief rule base (BRB) can effectively address small sample information under uncertainty by aggregating monitoring data and expert knowledge. Thus, a BRB-based forecasting method for the error coefficient of the SIMU prediction is proposed. In order to make full use of the input information, the information transformation accuracy is improved and the information loss is reduced during the index transformation process, a new calculation method of matching degrees is proposed according to the characteristics of the impulse output of SIMU, which can improve the accuracy of the model. Finally, the effectiveness of the proposed method is verified by an example of a type of SIMU accelerometer.

Key words: strapdown inertial measurement unit (SIMU), error coefficient, belief rule base (BRB), expert knowledge, matching degree

中图分类号:

TP202

董昕昊, 周志杰, 张友民, 冯志超, 曹友. 基于置信规则库的捷联惯组误差系数预测方法[J]. 系统工程与电子技术, 2020, 42(12): 2867-2874.

Xinhao DONG, Zhijie ZHOU, Youmin ZHANG, Zhichao FENG, You CAO. Forecasting method of the error coefficient for SIMU based on belief rule base[J]. Systems Engineering and Electronics, 2020, 42(12): 2867-2874.

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参考等级	VS	S	M	H	VH
参考值	3 278	3 400	3 520	4 200	6 600

参考等级	VS	S	M	H	VH
参考值	652	700	1 000	1 600	3 900

参考等级	S	M	L
参考值	2 151 835	2 151 920	2 152 049

序号	规则权重	属性		误差系数置信度分配
序号	规则权重	x₁	x₂	误差系数置信度分配
1	1	VS	VS	(0 0.1 0.9)
2	1	VS	S	(0 0.2 0.8)
3	1	VS	M	(0 0.3 0.7)
4	1	VS	H	(0 0.35 0.65)
5	1	VS	VH	(0 0.4 0.6)
6	1	S	VS	(1 0 0)
7	1	S	S	(0 0.5 0.5)
8	1	S	M	(0 0.6 0.4)
9	1	S	H	(0 0.7 0.3)
10	1	S	VH	(0 0.8 0.2)
11	1	M	VS	(0 0.9 0.1)
12	1	M	S	(0 1 0)
13	1	M	M	(0 0.5 0.5)
14	1	M	H	(0.1 0.9 0)
15	1	M	VH	(0.2 0.8 0)
16	1	H	VS	(0.25 0.75 0)
17	1	H	S	(0.3 0.7 0)
18	1	H	M	(0.4 0.6 0)
19	1	H	H	(0.5 0.5 0)
20	1	H	VH	(0.6 0.4 0)
21	1	VH	VS	(0.7 0.3 0)
22	1	VH	S	(0.8 0.2 0)
23	1	VH	M	(0.9 0.1 0)
24	1	VH	H	(0.95 0.05 0)
25	1	VH	VH	(1 0 0)
—	—	—	—	——

序号	规则权重	属性		误差系数置信度分配
序号	规则权重	x₁	x₂	误差系数置信度分配
1	0.61	VS	VS	(0 0 1)
2	0.99	VS	S	(0.1 0.9 0)
3	0.39	VS	M	(0.88 0.05 0.07)
4	0.42	VS	H	(0.75 0.20 0.05)
5	0.09	VS	VH	(0.21 0.29 0.50)
6	0	S	VS	(0.36 0.56 0.80)
7	0.17	S	S	(0.99 0 0.01)
8	0.56	S	M	(0.92 0.05 0.03)
9	0.48	S	H	(0.53 0.30 0.17)
10	0.96	S	VH	(0.28 0.40 0.32)
11	1	M	VS	(0.04 0.64 0.31)
12	0.08	M	S	(0.21 0.79 0)
13	0.81	M	M	(0.59 0.24 0.17)
14	0.44	M	H	(0.49 0.35 0.16)
15	0.2	M	VH	(0.52 0.48 0)
16	0.01	H	VS	(0.31 0.66 0.03)
17	0.71	H	S	(0.39 0.34 0.27)
18	0.97	H	M	(0.57 0.28 0.15)
19	0.51	H	H	(0.69 0.21 0.10)
20	0.82	H	VH	(0.93 0.06 0.01)
21	0.71	VH	VS	(0.97 0 0.03)
22	0.07	VH	S	(0.56 0.39 0.05)
23	0.56	VH	M	(0.37 0.30 0.33)
24	1	VH	H	(0.67 0.25 0.08)
25	0.94	VH	VH	(0.99 0.01 0)
—	—	—	—	——