智能办公环境温度控制方法

Temperature control approach in intelligent office environment

针对变频空调技术参数固定不能适应智能办公环境变化的问题,为提高环境温度的舒适度,提出一种新的变频空调温度控制方法。该方法引入多智能体(Agent)技术设计温度模糊控制结构,确定输入输出变量及其模糊集,然后引入动作回报值改进模糊Q学习算法,由推理Agent执行算法学习手动调节空调的动作、修改模糊规则。将得到的优化模糊规则用于环境温度的控制。实验结果表明,与常规模糊温度控制方法相比,该控制方法缩短了空调的响应时间,减少了超调量。

The parameters of inverter air-conditioner are fixed, which cannot adapt to changed intelligent office environment. This paper proposed a new air-conditioner control approach in order to improve the comfort of the ambient temperature. Multi-Agent technology was introduced, and input and output variables and their fuzzy sets were given, and then the fuzzy Q-learning algorithm introduced rewards was proposed, which was executed by reasoning Agent to learn manually adjusting the air-conditioner action, and modify the fuzzy rules, so the fuzzy rules were optimized. Finally the optimization fuzzy rules were applied to control ambient temperature. The experimental result shows that the response time and overshoot of the air-conditioner are less than the conventional fuzzy temperature control approach.