模糊控制空调作业,变频空调的模糊控制系统的设计

变频

空调

模糊

控制

专业：测控技术与仪器

班级：0901

姓名：贾军强

学号：0906070123

变频空调的模糊控制系统的设计

摘要

随着人民生活水平的不断提高，家用空调器的需求量逐年增加。变频空调由于性能优异，节省能源等特点，逐渐成为各大空调器生产企业的发展方向，变频技术也日渐得到各空调器厂商的重视。

模糊控制变频空调器的优点是高效节能，起动电流小，工作噪声小，温度控制精度高，算法简单，控制简单等，可以创造出人体适应的温度环境。采用无刷直流电机作为压缩机的驱动电机，能获得更好的控制性能，能效比高，且使用寿命更长。

本论文通过对变频空调模糊控制系统的设计，达到了预期的要求。通过对模糊控制的基本理论以及模糊控制器的基本结构的阐述，认识了设计模糊控制的基本方法，并联系变频空调的实际，设计出适合变频空调使用的模糊控制器。

关键词变频空调；模糊控制

design for fuzzy control system of variable-frequency air-condition

Abstract

With the improvement of people's standard of living, home air-conditioner will be more and more required. Recently, inverter air conditioner, with the merits of high performance and energy conservation, has become the developing direction of the main air conditioner manufacturing enterprises. Inverter technique has been increasingly focused on by the manufacturers.

The advantage of fuzzy-control inverter air-condition lies on the high efficiency, high precision of temperature control, simple arithmetic, simple control theory, low start up current and low noise. Furthermore, using brushless DC motor as the compressor can get high efficiency and long life span.

The variable-frequency air-condition fuzzy controller are the major object of control in the design.It contains the basic theory of fuzzy control the basic structure of fuzzy logic controller,cognizes the method of fuzzy control,and contacts the actual applications ,designs a fuzzy logic controller of variable-frequency air-condition. Keywords variable-frequency air-condition; fuzzy control

变频空调的各项要求：

输入：温度18-40℃范围内分为七个论域，NB NM NS ZE PS PM PB；隶属度函数满足高斯分布；

输入误差：温度变化率-2 ~2℃范围内分为七个论域，NB NM NS ZE PS PM PB；隶属度函数满足高斯分布；

输出：变频空调输出的控制信号在24~30℃范围内分为七个论域，NB NM NS ZE PS PM PB，隶属度函数为常数1。

模糊推理过程，output=输入隶属度函数值*输出论域的中心值。

模糊控制规则:

1. 输入图：

程序为：x = (18:0.1:40)';

y0 = gaussmf(x, [2 18]); y1 = gaussmf(x, [2 21.7]); y2 = gaussmf(x, [2 25.4]); y3 = gaussmf(x, [2 29]); y4 = gaussmf(x, [2 32.7]); y5= gaussmf(x, [2 36.3]); y6= gaussmf(x, [2 40]); plot(x,[y0 y1

y2 y3 y4 y5 y6]);

2. 误差图： 程序为： ex= (-2:0.1:2)';

ey0 = gaussmf(ex, [0.5 -2]); ey1 = gaussmf(ex, [0.5 -1.4]); ey2 = gaussmf(ex, [0.5 -0.7]);

ey3 = gaussmf(ex, [0.5 0]);

ey4 = gaussmf(ex, [0.5 0.7]);

ey5= gaussmf(ex, [0.5 1.4]);

ey6= gaussmf(ex, [0.5 2]);

plot(ex,[ey0 ey1 ey2 ey3 ey4 ey5 ey6]);

3.程序为；

x=19;

ex=0;

% define input type in fuzzy zone

y0 = gaussmf(x, [2 18]);

y1 = gaussmf(x, [2 21.7]);

y2 = gaussmf(x, [2 25.4]);

y3 = gaussmf(x, [2 29]);

y4 = gaussmf(x, [2 32.7]);

y5= gaussmf(x, [2 36.3]);

y6= gaussmf(x, [2 40]);

a=[y0 y1 y2 y3 y4 y5 y6];

b=max(a);

% caculate input in fuzzy zone,get input_type and input_authorityvalue if x<=40 & x>=18

if b==a(1)

type='NB';

authorityvalue=y0;

elseif b==a(2)

type='NM';

authorityvalue=y1;

elseif b==a(3)

type='NS';

authorityvalue=y2;

elseif b==a(4)

type='ZE';