Against the backdrop of the rapid development of metal smelting processes, the requirements for reaction temperature control are gradually increasing, and the temperature control system for porous media burners based on advanced simplified instruction embedded processors has been developed. In this burner, the fuel is heated using a porous medium for conduction, which generates various complex data during operation and can overload conventional algorithms. To reduce the difficulty of algorithm operation, this study introduced an adaptive database into the proportional integral differential algorithm to classify data and establish a load balancer in the advanced reduced instruction algorithm, which is convenient for embedded processing of large amounts of data. To avoid the algorithm falling into local optima, this study merged the digital output module with it during temperature control to generate a fusion system. Finally, this study conducted experiments on the Porbu dataset and compared it with three systems such as generalized predictive control to verify the superiority of the fusion system. The temperature control accuracy of the four systems was 99.7%, 97.2%, 96.1%, and 93.5%, respectively, indicating that the efficiency of the fusion system performs the best among the four systems. The energy consumption of this system was 0.038 kWh, which performs best among the four systems. The experimental results indicate that the fusion system proposed in this study has the strongest performance and is suit-able for precise temperature control of porous media burners.