针对太阳能-空气源热泵供暖系统运行环境复杂多变,模糊控制器的设计高度依赖人工经验的问题,提出一种基于自适应神经模糊推理系统（ANFIS）改进的模糊控制方法。该方法利用ANFIS在复杂系统建模中的优势,结合供暖系统温度响应特性和实际运行数据,建立联合供暖系统变工况ANFIS模型,生成与系统性能适配的模糊规则库并传递给模糊控制器执行。Matlab/Simulink仿真对比试验表明,与单一的模糊控制相比,该方法的控制精度提高了17.65%,调节时间缩短了36.4%,具有更高的控制精度和响应速度。
Abstract
An improved fuzzy control method based on adaptive neuro-fuzzy inference system （ANFIS） is proposed in order to address the issue that the operation environment of solar-air source heat pump heating systems is complex and variable, and the design of fuzzy controller heavily depends on artificial experience. This technique establishes the off-working condition ANFIS model of the combined heating system, generates the fuzzy rule base that adapts to the system performance, and passes it to the fuzzy controller for execution. It makes use of the benefits of ANFIS in complex system modeling, along with the temperature response characteristics of the heating system and the actual operation data. According to the findings of the Matlab/Simulink simulation, the control precision and response speed of this approach are greater by 17.65% and 36.4%, respectively, when compared to a single fuzzy control.
关键词
太阳能 /
空气源热泵 /
联合供暖 /
模糊控制 /
温度控制 /
ANFIS
Key words
solar energy /
air source heat pump /
district heating /
fuzzy control /
temperature control /
ANFIS
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基金
国家自然科学基金（62365015）内蒙古自然科学基金（2023MS05047; 2021LHBS05005）; 内蒙古自治区直属高校基本科研业务费项目（2023RCTD011; 2023YXXS012）; 内蒙古自治区高等学校科学技术研究项目（NJZY21393）
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