Intelligent fuzzy inference method for generating UUV hull parameters

参数	范围
艏部长度a/m	0.2～1.3
平行中体长度b/m	3.0～5.0
艉部长度c/m	0.5～1.5
艏部锐度因子n	1～4
艉部离去角θ/(°)	10～45
中体直径d/m	0.533
主机功率P_S/W	200～500
电池容量Q/Wh	3 000～8 000
运动黏度u/(m²·s⁻¹)	1.188×10⁻⁶
额定航速v/kn	4
海水密度ρ/（kg·m⁻³）	1 025
放电深度p₁/%	90
载荷功率p_D/W	100

Table 2. Training steps of fuzzy inference algorithm

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Table 2. Training steps of fuzzy inference algorithm

算法：UUV生成解的T-S学习
输入：由遗传算法生成满足约束的4 000个可行解
输出：符合约束条件且满足f₁ + f₂>ε的所有解
Step1：计算前件参数
for m=1 to R
确定隶属函数中心点c_r,
计算隶属度值$u_{{A_i}}^k({x_i})$
end for
Step2：for k=1 to K
确定最小隶属度值u_min
计算所有样本在整个区间中的最小值U_min作为规则输出H
end for
Step3：计算规则后件参数β
Step4：计算优化参数Y
Step5：依据式（12）和式（13）计算航速和航程的评价分值，输出f₁ + f₂ > ε的所有解

Table 3. UUV classification by US Navy
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Table 3. UUV classification by US Navy
UUV分类直径/m 排水量/kg
便携型 0.076～0.229 ＜45.359
轻型 0.325 ＜226.796
重型 0.533 ＜1 360.777
巨型＞0.914 ＜9 071.847

Table 4. The optimized solution for the membership degree scores of the speed and range of UUV

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Table 4. The optimized solution for the membership degree scores of the speed and range of UUV

组别	方法
	遗传算法			模糊推理
	f₁	f₂	f₁+ f₂	f₁	f₂	f₁+f₂
50	74.59	93.91	168.49	72.64	97.98	170.61
49	75.63	92.84	168.48	73.58	96.98	170.56
48	73.94	94.40	168.34	73.57	96.96	170.52
47	71.15	97.12	168.27	73.40	97.10	170.51
46	72.57	95.69	168.26	72.88	97.39	170.27
45	71.09	97.08	168.16	73.55	96.70	170.25
44	74.18	93.80	167.98	72.45	97.70	170.15
43	70.58	97.26	167.84	74.28	95.75	170.03
42	72.79	94.79	167.58	73.56	96.45	170.01
41	73.94	93.57	167.52	73.79	96.21	170.00
50组均值	71.57	94.53	166.10	72.91	96.45	169.36

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Junbin GONG, Pengjiu WANG, Hao WANG, Meng YANG. Intelligent fuzzy inference method for generating UUV hull parameters[J]. Chinese Journal of Ship Research, 2024, 19(6): 56

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