PID and fuzzy logic in temperature control system
PID and fuzzy logic in temperature control system
复制标题
温度控制系统中的PID和模糊逻辑
DOI：
10.1109/icceee.2013.6633927
复制
发表时间：
2013
期刊：
影响因子：
--
通讯作者：
W. Taha
中科院分区：
文献类型：
--
作者：
M. Elnour;W. Taha
本文提出了一种温度控制系统的人工智能控制方法，适用于实验室设备（例如烤箱和培养箱）等低温应用。所提出的设计使用模糊逻辑作为控制方法，将模拟加热器的温度保持在所需点。基于微控制器的电路用于从传感器获取数据、驱动热元件并与计算机工作站通信。 MATLAB 模糊逻辑控制器经过设计、测试和调整来控制电路。通过将模糊逻辑控制器与传统比例积分微分 (PID) 控制器在对所需设定值的响应速度、固定设定点的超调以及抗干扰鲁棒性方面进行比较，在多种情况下评估模糊逻辑控制器的性能。与PID相比，FLC对设定的响应速度更快，并且对抗外部干扰更加稳定。 FLC和PID都忽略了超调值和稳态误差，但FLC在高设定点有明显的偏差。
This paper proposed an artificial intelligent control method for temperature control system and is suitable for low temperature applications such as laboratory equipments (e.g. ovens and incubators). The proposed design uses fuzzy logic as a control method that maintains the temperature of simulated heater to the desired point. Microcontroller based circuit is built to acquire data from sensor, actuate heat element and communicate with computer workstation. MATLAB fuzzy logic controller is designed, tested, and tuned to control the circuit. The Fuzzy Logic Controller performance is evaluated in several situations by comparing it with conventional Proportional Integral Derivative (PID) controller in terms of speed of response to the desired setting value, overshoot in fixed set point and robustness against disturbance. FLC is fast in response to the setting with compare to PID, and more stable against external disturbance. Both of FLC and PID have neglected overshoot value and steady state error, but FLC has noticeable deviation in high set points.