摘要
与传统的PID控制相比,模糊控制更节能省电、制冷制热也更快,但也存在一定的缺陷,如过于依赖模糊控制规则的专家库,精度不高,以及温度突变时舒适感不太好等。用遗传算法优化模糊控制,可解决此问题,能更快更稳定地达到预设温度。在其他同行研究的基础上,仿真时增加了消除静态误差的积分器和消除可能震荡的史密斯比较器,仿真追踪效果显示控制效果得到进一步优化。
For the control of Inverter Air-Conditioning , fuzzy control is more efficient than the traditional PID control, and can be faster to reach the set temperature. However, it also has some detects： the fuzzy control rules are too dependent on the expert database, the accuracy is not high, and people＇ s comfort are not so good when temperature jumps. Genetic Algorithm can solve the problem of fuzzy control, which can reach the temperature faster and more stably. Compared with other studies, this paper adds inte- grator and Smith comparator to eliminate static error and poential shocks. And the result of matlab simulation shows that integrator and Smith comparator can bring better control effect.
作者
李雅琼
李梅
LI Yaqiong LI Mei(Fuyang Vocational And Technical College, Fuyang 236000, Chin)
出处
《东莞理工学院学报》
2017年第1期41-47,共7页
Journal of Dongguan University of Technology
基金
阜阳职业技术学院校级科研项目(2014KYXM07)
安徽省级质量工程机电一体化技术教学团队(2014jxtd058)
安徽省高职教育创新发展行动计划机电一体化骨干专业建设XM01
关键词
变频空调
遗传算法
模糊控制
MATLAB仿真
inverter air-conditioning
genetic algorithm
fuzzy control
Matlab simulation
