Applied Thermal Engineering ( IF 6.4 ) Pub Date : 2021-06-16 , DOI: 10.1016/j.applthermaleng.2021.117234 Hui Liang , Ze-Kang Sang , Yun-Zhi Wu , You-Hua Zhang , Rui Zhao
In complex outdoor conditions, radical weather changes can sometimes undermine the precision of temperature control systems, mainly because conventional heater controllers lack the ability to adapt to unpredictable parametric variations. In this paper, a heater auto-tuned by a PID neural network was proposed. Without knowing the range of weather variation in advance, the PID neural network self-adapts to weather changes and other kinds of disturbances, using a function that is driven by the back propagation algorithm. The temperature-control performance of this heater was numerically studied under a variety of outdoor conditions. A classical PID controlled heater was tuned under conditions as same as the PIDNN controller was pre-trained, and their performances were compared. The results showed that the PID neural network-controlled heater adapted well to weather and climate changes. It consistently maintained the temperature of the controlled unit with an overshoot of less than 0.2 °C, and it had a settling time of less than 32 s. By contrast, the PID controlled heater failed to achieve precise temperature-control when the wind speed rose at a rate greater than 1.5 m/s per hour. When the electrical resistance of the heater was temperature-dependent, the PIDNN controller managed to stabilize the temperature in less than 40 s. As for fast disturbances, such as sudden rain, the overshoot of the PIDNN was less than 1 °C, and the settling time was about 20 s.
中文翻译:
复杂室外条件下PID神经网络控制加热器的高精度控温性能
在复杂的室外条件下,剧烈的天气变化有时会破坏温度控制系统的精度,主要是因为传统的加热器控制器缺乏适应不可预测的参数变化的能力。在本文中,提出了一种由 PID 神经网络自动调整的加热器。在事先不知道天气变化范围的情况下,PID 神经网络使用由反向传播算法驱动的函数来自适应天气变化和其他类型的干扰。在各种室外条件下对该加热器的温度控制性能进行了数值研究。在与 PIDNN 控制器相同的条件下对经典的 PID 控制加热器进行了调整,并对它们的性能进行了比较。结果表明,PID 神经网络控制的加热器能很好地适应天气和气候变化。它始终保持受控单元的温度,过冲小于 0.2 °C,并且稳定时间小于 32 秒。相比之下,当风速以每小时 1.5 m/s 以上的速度上升时,PID 控制的加热器无法实现精确的温度控制。当加热器的电阻与温度有关时,PIDNN 控制器设法在不到 40 秒的时间内稳定温度。对于突然下雨等快速扰动,PIDNN 的超调量小于 1 °C,稳定时间约为 20 s。并且它的稳定时间小于 32 s。相比之下,当风速以每小时 1.5 m/s 以上的速度上升时,PID 控制的加热器无法实现精确的温度控制。当加热器的电阻与温度有关时,PIDNN 控制器设法在不到 40 秒的时间内稳定温度。对于突然下雨等快速扰动,PIDNN 的超调量小于 1 °C,稳定时间约为 20 s。并且它的稳定时间小于 32 s。相比之下,当风速以每小时 1.5 m/s 以上的速度上升时,PID 控制的加热器无法实现精确的温度控制。当加热器的电阻与温度有关时,PIDNN 控制器设法在不到 40 秒的时间内稳定温度。对于突然下雨等快速扰动,PIDNN 的超调量小于 1 °C,稳定时间约为 20 s。