基于BP神经网络的中央空调温湿度自适应控制系统

针对空调系统大惯性、大滞后的特点和常规PID控制所存在的不足,介绍了利用BP神经网络误差反传机制,探讨建立在BP神经网络基础上对温湿度的自适应控制。利用2个BP神经网络NNC和NNI,分别做控制器和辨识器,通过相互间误差的传递,对变风量空调系统中送风温湿度的控制问题,具有更快、更稳定的控制效果。在实际运用中,结合Lonworks总线技术给出系统的硬件和软件设计,使得系统智能节点可自由通信,便于安装调试且能对温湿度进行实时监控。该设计使中央空调控制系统的整体性能大为改善。

Temperature and Humidity Adaptive Control in Centre Air-conditioning System Based on BP Neural Networks

Aimed at the specialty of the airconditioning system:great inertia,great lag,and the defect of the usual PID control,introduced using the error backward characteristic of BP neural network,discussed the temperature and humidity adaptive control based on BP neural network.Two networks,NNC and NNI,used as controller and identifier.Make use of the error contact in one another,to solve the temperature and humidity problem control in the centre air-conditioning system.Combine the Lonworks-bus technology,gave out the hardware and software design in practice.By this way,the intelligent-point can communicate freely,install conveniently and monitor temperature and humidity in time,The design will improve the integral-capability of central air-conditioning control system greatly.