| 摘要: |
| 直膨式空调系统温湿度控制过程高度耦合，造成传统方法下室内空气温湿度的同时精确控制较难实现。本研究基于模糊PD控制逻辑，利用稳态ANN模型建立新型温湿度同时控制算法，根据实时温湿度的控制误差计算所需的显、潜冷量，输出风机、压缩机转速，实现温湿度的同时控制。针对建立的新型控制算法，进行了控制性能验证实验，命令跟随实验结果表明，在新型控制算法的控制下，空气干球与湿球温度设定值改变后在720 s内被稳定在新的设定值，误差在±0.2 ℃以内；负荷干扰实验结果表明，在有负荷扰动的条件下，控制器在干湿球温度偏离设定值0.5 ℃后迅速响应，并在600 s内将干湿球温度控制到设定值，波动不超过0.2 ℃。因此本文建立的新型控制方法可以实现使用变速直膨式系统进行室内空气温湿度同时控制。 |
| 关键词: 空气调节系统 人工神经网络 模糊PD 温湿度同时控制 |
| DOI： |
| 投稿时间：2017-07-19
|
| 基金项目: |
|
| Simultaneous Control Strategy of Temperature and Humidity in Variable Speed Direct-expansion Air-conditioning System Based on Steady-state ANN Aided Fuzzy PD |
|
Li Zhao, Cui Lingchuang, Chen Jianbo
|
| (School of Environment and Architecture, University of Shanghai for Science and Technology) |
| Abstract: |
| The temperature and humidity control processes in a variable-speed direct-expansion air-conditioning (DX A/C) system are significantly coupled, which makes it difficult to realize the precise control of indoor air temperature and humidity simultaneously when traditional methods are used. Based on a fuzzy proportional-derivative (PD) control logic and steady-state artificial neural network (ANN) model, a novel temperature and humidity simultaneous control strategy was developed in this study. This control strategy uses the updating temperature and humidity errors to calculate the actually required control signals, the compressor, and the fan speeds to achieve simultaneous control of the temperature and humidity. Controllability tests were carried out to examine the performances of the novel controller including command following tests and disturbance rejection tests. The command following test results showed that the air dry-bulb and wet-bulb temperatures can be controlled to their new set points within 720 s with an oscillation of no more than ± 0.2 ℃ after the set points are changed. The disturbance rejection test results showed that, when a disturbance is introduced into the cooling load, the controller can respond immediately if the temperature differences between the set points and the present values reach 0.5 ℃ and maintain the dry-bulb and wet-bulb temperatures at their set points within 600 s, with a moderate oscillation of ± 0.2 ℃. Thus, the experimental results suggest that the novel control strategy established in this study can realize the simultaneous control of the indoor air temperature and humidity using a variable-speed DX A/C system. |
| Key words: air conditioning system artificial neural network(ANN) fuzzy PD simultaneous control of temperature and humidity |
