Affected by COVID-19, the demand for nucleic acid detection at home and abroad is gradually increasing, and nucleic acid detection generally requires qualitative analysis of PCR amplification products. At present, the commonly used analysis method of amplification products is agarose gel electrophoresis. In this paper, the whole process of agarose gel production is analyzed, and a fuzzy-neural network PID joint control scheme is proposed for different concentrations of agarose solution reagents to realize different temperature control strategies for different stages of the same concentration solution reagents and different concentration solution reagents. For the glue-making process with the same concentration of reagent, fuzzy control is used to improve the heating power when the temperature difference is large. On the contrary, the BP neural network is used to train the best PID parameter for gelatinizing at the current concentration, so as to realize the temperature control of the whole process of agarose heating and gelatinizing at different concentrations. The sol instrument experimental platform built by this algorithm realizes the glue preparation experiment of different concentration solution and the remelting experiment of the same concentration solution, which achieves the temperature control precision of ±1 ℃ and achieves a better glue preparation effect.