Intelligent Pet House Environment Control System Based on Decoupling Fuzzy Neural Network

In recent years, the number of pets in China has increased, and intelligent pet houses have developed rapidly. However, most intelligent pet houses use traditional PID control methods to control environmental parameters. However, the air conditioning process often has strong coupling and time-varying characteristics. The traditional control method is too rough, and there are problems such as high energy consumption and poor anti-interference ability. In this paper, a design scheme of intelligent pet house environment control system based on decoupled fuzzy neural network is proposed. The scheme combines multivariable decoupling model, fuzzy control and neural network control algorithm to solve the difficulty of system control. The experimental data show that the temperature and humidity control overshoot of the algorithm is reduced by 66.9% and 56.6% respectively compared with the conventional PID control, and the control time is shortened by 38.44% and 35.39% respectively compared with the original PID control, which improves the problems existing in the traditional control.