matlab实现车速模糊控制算法
时间: 2023-06-29 08:15:23 浏览: 155
车速模糊控制算法(Fuzzy Logic Control)可以使用Matlab进行实现。下面是一个简单的车速模糊控制算法的示例代码:
```matlab
% 设定模糊变量的范围
speedRange = [0 120];
errorRange = [-30 30];
deltaRange = [-20 20];
% 定义模糊集
speed = newfis('speed');
speed = addvar(speed, 'input', 'speed', speedRange);
speed = addmf(speed, 'input', 1, 'slow', 'trimf', [0 0 60]);
speed = addmf(speed, 'input', 1, 'medium', 'trimf', [0 60 120]);
speed = addmf(speed, 'input', 1, 'fast', 'trimf', [60 120 120]);
delta = newfis('delta');
delta = addvar(delta, 'input', 'delta', deltaRange);
delta = addmf(delta, 'input', 1, 'negative', 'trimf', [-20 -20 0]);
delta = addmf(delta, 'input', 1, 'zero', 'trimf', [-20 0 20]);
delta = addmf(delta, 'input', 1, 'positive', 'trimf', [0 20 20]);
error = newfis('error');
error = addvar(error, 'input', 'error', errorRange);
error = addmf(error, 'input', 1, 'negative', 'trimf', [-30 -30 0]);
error = addmf(error, 'input', 1, 'zero', 'trimf', [-30 0 30]);
error = addmf(error, 'input', 1, 'positive', 'trimf', [0 30 30]);
output = newfis('output');
output = addvar(output, 'output', 'output', [-20 20]);
output = addmf(output, 'output', 1, 'negative', 'trimf', [-20 -20 0]);
output = addmf(output, 'output', 1, 'zero', 'trimf', [-20 0 20]);
output = addmf(output, 'output', 1, 'positive', 'trimf', [0 20 20]);
% 设定规则
ruleList = [1 1 1 1 2;
2 2 2 1 1;
3 3 3 1 1;
1 3 1 2 2;
2 1 1 2 2;
3 2 2 2 1;
1 2 1 2 2;
2 3 2 2 1;
3 1 3 2 2];
% 运行模糊控制系统
speedInput = 80;
errorInput = -10;
deltaInput = 5;
outputValue = evalfis([speedInput errorInput deltaInput], {speed, error, delta, output}, ruleList);
disp(outputValue);
```
这段代码定义了三个输入变量(车速、误差和误差变化量)和一个输出变量(控制量)。通过设定模糊集和规则,可以实现车速模糊控制算法,最后通过调用`evalfis`函数得到输出变量的值。
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