双输入单输出模糊控制器详细设计流程
一、模糊语言确定及等级划分
如表1是模糊语言的确定,认为确定
人类模糊语言 | 负大 | 负中 | 负小 | 负零 | 正零 | 正小 | 正中 | 正大 |
符号 | NL | NM | NS | N0 | P0 | PS | PM | PL |
对于人类模糊语言,每一个语言(例如:负大)分成 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 这些等级。
二、变量隶属度及其表格
E μ(E) 语言 |
-6 |
-5 |
-4 |
-3 |
-2 |
-1 |
0 |
1 |
2 |
3 |
4 |
5 |
6 |
E1 NL |
1.0 |
0.8 |
0.4 |
0.1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
E2 NM |
0.2 |
0.7 |
1 |
0.7 |
0.2 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
E3 NS |
0 |
0 |
0.1 |
0.5 |
1 |
0.8 |
0.3 |
0 |
0 |
0 |
0 |
0 |
0 |
E4 ZO |
0 |
0 |
0 |
0 |
0.1 |
0.6 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
E5 PS |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0.6 |
0.1 |
0 |
0 |
0 |
E6 PM |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0.1 |
0.2 |
0.7 |
1 |
0.2 |
E7 PL |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0.1 |
0.1 |
0.4 |
0.8 |
E的隶属度表格
EC u(EC) 语言 |
-6 |
-5 |
-4 |
-3 |
-2 |
-1 |
0 |
1 |
2 |
3 |
4 |
5 |
6 |
E1 NL |
1.0 |
0.8 |
0.4 |
0.1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
E2 NM |
0.2 |
0.7 |
1 |
0.7 |
0.2 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
E3 NS |
0 |
0 |
0.1 |
0.5 |
1 |
0.8 |
0.3 |
0 |
0 |
0 |
0 |
0 |
0 |
E4 ZO |
0 |
0 |
0 |
0 |
0.1 |
0.6 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
E5 PS |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0.6 |
0.1 |
0 |
0 |
0 |
E6 PM |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0.1 |
0.2 |
0.7 |
1 |
0.2 |
E7 PL |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0.1 |
0.1 |
0.4 |
0.8 |
EC的隶属度表格
U u(U) 语言 |
-6 |
-5 |
-4 |
-3 |
-2 |
-1 |
0 |
1 |
2 |
3 |
4 |
5 |
6 |
E1 NL |
1.0 |
0.8 |
0.4 |
0.1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
E2 NM |
0.2 |
0.7 |
1 |
0.7 |
0.2 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
E3 NS |
0 |
0 |
0.1 |
0.5 |
1 |
0.8 |
0.3 |
0 |
0 |
0 |
0 |
0 |
0 |
E4 ZO |
0 |
0 |
0 |
0 |
0.1 |
0.6 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
E5 PS |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
0.6 |
0.1 |
0 |
0 |
0 |
E6 PM |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0.1 |
0.2 |
0.7 |
1 |
0.2 |
E7 PL |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0.1 |
0.1 |
0.4 |
0.8 |
U的隶属度表格
根据这个隶属度表格,结合MATLAB,自己就可以写个小程序,从而画出各个等级的对于某个语言的隶属函数图像。
如下是示意的隶属度函数图像:
三、模糊语言控制规则及表示方法
根据人类描述的模糊语言控制规则可以很容易得出:IF E=Ei and EC=ECj then U=Uij ,也就是可以用数学模糊表示为:R=∪(Ei