智能家居室内温度远程优化控制仿真研究

Intelligent Household Indoor Temperature Remote Control Simulation Study

对智能家居室内温度进行准确控制,可以改善智能家居室内的体验效果。在进行智能家居室内温度控制时,应对当前温度采样值是否合理进行判断,并将判断信息进行发送,而传统方法是通过时间触发控制方法进行远程在线控制家居温度控制,无法准确判断当前温度是否合理,同时所需的节点多、稳定性差、而且会造成不必要的能源浪费,降低了智能家居室内温度控制的效果。提出一种随机变异粒子群算法的智能家居室内温度远程优化控制方法。根据无线传感温度控制节点和事件触发条件决定当前采样值是否发送,搜索智能家居空间粒子的位置和速度,在优化模拟家居温度控制粒子群的过程中,不断改变粒子位置和速度,直到搜寻出适用于智能家居的最优温度,实现智能家居温度在线调节和远程控制。仿真结果表明,提出的改进方法能够有效地实现智能家居温度高精度的远程控制。

It can improve the indoor experience effect of intelligent home living to control indoor temperature ac- curately. The indoor temperature control should judge whether the current temperature sampling value is reasonable and send the judgement information. However, traditional method makes remote on - line control to home living temperature through time - triggered control method. It cannot judge whether the current temperature sampling value is reasonable and leads to overmuch needed node, poor stability, and unnecessary energy waste. Therefore, it reduces the indoor temperature control effect. In this paper, we propose an optimization method for remote control of indoor temperature in intelligent home living based on random variation PSO algorithm. The method decides whether the current sampling value sent according to temperature control node of wireless sensing and event triggering condition to search the position and speed of space particle in intelligent home living. Then it changes the particle position and speed constantly during the process of optimizing simulation on particle swarm of temperature control in home living. Finally, we achieve the temperature online adjustment and remote control of temperature in intelligent home living until seeking out the optimal temperature suitable for intelligent home living. The simulation results show that the modified method can achieve the high precision remote control of intelligent home living temperature.