Fuzzy Q-learning Control for Temperature Systems

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Show simple item record Chen, Yeong-Chin Hung, Lon-Chen Syamsudin, Mariana 2023-01-09T13:34:26Z 2023-01-09T13:34:26Z 2023-01-09
dc.description IEEE Computer Society en_GB
dc.description.abstract 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. en_GB
dc.subject reinforcement learning en_GB
dc.subject IoT en_GB
dc.subject fuzzy q-learning en_GB
dc.subject multi-agent en_GB
dc.subject temperature en_GB
dc.title Fuzzy Q-learning Control for Temperature Systems en_GB

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