Fuzzy Q-learning Control for Temperature Systems

In this paper, the reinforcement learning algorithm applied to temperature control of the internet of things (IoT), which aims to develop a multi-purpose intelligent micro-power control switch to achieve advanced temperature control research. This paper is based on the fuzzy Q-learning PID control algorithm based on reinforcement learning, with LinkIt Smart 7688 Duo platform. The error value between the set temperature and the actual sensed temperature is exposed to the reinforcement learning PID control operation. Specifically, a temperature sensor will provide temperature feedback to the LinkIt Smart 7688 Duo in order to achieve the stated temperature control. Finally, the suggested control approach will be compared to PID control to illustrate its efficacy and performance.