python实现模糊控制算法

模糊控制算法是一种基于模糊逻辑的控制方法，可以应用于各种控制系统中。Python中可以使用scikit-fuzzy库来实现模糊控制算法。

具体步骤如下：
1. 确定输入和输出变量，并定义它们的模糊集合和隶属函数。
2. 定义规则库，即输入变量和输出变量之间的关系。
3. 对输入变量进行模糊化，将其转换为隶属度函数。
4. 使用模糊推理方法，根据规则库和输入变量的隶属度函数计算输出变量的隶属度函数。
5. 对输出变量的隶属度函数进行去模糊化，得到具体的输出值。

以下是一个简单的模糊控制器示例代码：

import numpy as np
import skfuzzy as fuzz
from skfuzzy import control as ctrl

# 定义输入和输出变量
error = ctrl.Antecedent(np.arange(-5, 6, 1), 'error')
delta_error = ctrl.Antecedent(np.arange(-5, 6, 1), 'delta_error')
output = ctrl.Consequent(np.arange(-10, 11, 1), 'output')

# 定义隶属函数
error['NB'] = fuzz.trimf(error.universe, [-5, -5, -2])
error['NM'] = fuzz.trimf(error.universe, [-4, -2, 0])
error['NS'] = fuzz.trimf(error.universe, [-1, 0, 1])
error['ZO'] = fuzz.trimf(error.universe, [-0.5, 0, 0.5])
error['PS'] = fuzz.trimf(error.universe, [0, 2, 4])
error['PM'] = fuzz.trimf(error.universe, [2, 5, 5])
error['PB'] = fuzz.trimf(error.universe, [2, 5, 5])

delta_error['NB'] = fuzz.trimf(delta_error.universe, [-5, -5, -2])
delta_error['NM'] = fuzz.trimf(delta_error.universe, [-4, -2, 0])
delta_error['NS'] = fuzz.trimf(delta_error.universe, [-1, 0, 1])
delta_error['ZO'] = fuzz.trimf(delta_error.universe, [-0.5, 0, 0.5])
delta_error['PS'] = fuzz.trimf(delta_error.universe, [0, 2, 4])
delta_error['PM'] = fuzz.trimf(delta_error.universe, [2, 5, 5])
delta_error['PB'] = fuzz.trimf(delta_error.universe, [2, 5, 5])

output['NB'] = fuzz.trimf(output.universe, [-10, -10, -5])
output['NM'] = fuzz.trimf(output.universe, [-7.5, -5, -2.5])
output['NS'] = fuzz.trimf(output.universe, [-5, -2.5, 0])
output['ZO'] = fuzz.trimf(output.universe, [-2.5, 0, 2.5])
output['PS'] = fuzz.trimf(output.universe, [0, 2.5, 5])
output['PM'] = fuzz.trimf(output.universe, [2.5, 5, 7.5])
output['PB'] = fuzz.trimf(output.universe, [5, 10, 10])

# 定义规则库
rule1 = ctrl.Rule(error['NB'] & delta_error['NB'], output['NB'])
rule2 = ctrl.Rule(error['NB'] & delta_error['NM'], output['NM'])
rule3 = ctrl.Rule(error['NB'] & delta_error['NS'], output['NS'])
rule4 = ctrl.Rule(error['NB'] & delta_error['ZO'], output['ZO'])
rule5 = ctrl.Rule(error['NB'] & delta_error['PS'], output['PS'])
rule6 = ctrl.Rule(error['NB'] & delta_error['PM'], output['PM'])
rule7 = ctrl.Rule(error['NB'] & delta_error['PB'], output['PB'])

rule8 = ctrl.Rule(error['NM'] & delta_error['NB'], output['NM'])
rule9 = ctrl.Rule(error['NM'] & delta_error['NM'], output['NS'])
rule10 = ctrl.Rule(error['NM'] & delta_error['NS'], output['ZO'])
rule11 = ctrl.Rule(error['NM'] & delta_error['ZO'], output['PS'])
rule12 = ctrl.Rule(error['NM'] & delta_error['PS'], output['PM'])
rule13 = ctrl.Rule(error['NM'] & delta_error['PM'], output['PB'])

rule14 = ctrl.Rule(error['NS'] & delta_error['NB'], output['NS'])
rule15 = ctrl.Rule(error['NS'] & delta_error['NM'], output['ZO'])
rule16 = ctrl.Rule(error['NS'] & delta_error['NS'], output['PS'])
rule17 = ctrl.Rule(error['NS'] & delta_error['ZO'], output['PM'])
rule18 = ctrl.Rule(error['NS'] & delta_error['PS'], output['PB'])

rule19 = ctrl.Rule(error['ZO'] & delta_error['NB'], output['ZO'])
rule20 = ctrl.Rule(error['ZO'] & delta_error['NM'], output['PS'])
rule21 = ctrl.Rule(error['ZO'] & delta_error['NS'], output['PM'])
rule22 = ctrl.Rule(error['ZO'] & delta_error['ZO'], output['PB'])
rule23 = ctrl.Rule(error['ZO'] & delta_error['PS'], output['PB'])

rule24 = ctrl.Rule(error['PS'] & delta_error['NB'], output['PS'])
rule25 = ctrl.Rule(error['PS'] & delta_error['NM'], output['PM'])
rule26 = ctrl.Rule(error['PS'] & delta_error['NS'], output['PB'])
rule27 = ctrl.Rule(error['PS'] & delta_error['ZO'], output['PB'])
rule28 = ctrl.Rule(error['PS'] & delta_error['PS'], output['PB'])

rule29 = ctrl.Rule(error['PM'] & delta_error['NB'], output['PM'])
rule30 = ctrl.Rule(error['PM'] & delta_error['NM'], output['PB'])
rule31 = ctrl.Rule(error['PM'] & delta_error['NS'], output['PB'])
rule32 = ctrl.Rule(error['PM'] & delta_error['ZO'], output['PB'])
rule33 = ctrl.Rule(error['PM'] & delta_error['PS'], output['PB'])

rule34 = ctrl.Rule(error['PB'] & delta_error['NB'], output['PB'])
rule35 = ctrl.Rule(error['PB'] & delta_error['NM'], output['PB'])
rule36 = ctrl.Rule(error['PB'] & delta_error['NS'], output['PB'])
rule37 = ctrl.Rule(error['PB'] & delta_error['ZO'], output['PB'])
rule38 = ctrl.Rule(error['PB'] & delta_error['PS'], output['PB'])

# 定义控制系统
system = ctrl.ControlSystem([rule1, rule2, rule3, rule4, rule5, rule6, rule7,
                              rule8, rule9, rule10, rule11, rule12, rule13,
                              rule14, rule15, rule16, rule17, rule18,
                              rule19, rule20, rule21, rule22, rule23,
                              rule24, rule25, rule26, rule27, rule28,
                              rule29, rule30, rule31, rule32, rule33,
                              rule34, rule35, rule36, rule37, rule38])

simulator = ctrl.ControlSystemSimulation(system)

# 输入变量赋值
simulator.input['error'] = -2
simulator.input['delta_error'] = 1

# 计算输出
simulator.compute()

# 输出结果
print(simulator.output['output'])

# 输出结果隶属度函数
output.view(sim=simulator)