Temperature control with fuzzy neural network

Abstract

Temperature control is a very common scene in industrial control. Combined with our previous research, the temperature control of drinking water is an important aspect of improving human health. Traditional temperature control methods include PID control, or considering multiple input factors, fuzzy control is used to adjust and control temperature. However, the deficiency is that the control accuracy is not ideal, and the feedback control is relative slow. It is a good idea and solution to optimize the condition of judging rules in temperature control by using the method of combining neural network and fuzzy control, and combining the optimization of algorithm to improve the precision and speed of temperature regulation. In this paper, the architecture of fuzzy neural network for drinking water temperature control and the algorithm design method are proposed, and the precision of temperature control and the improvement of regulation speed are provided.