Intelligent control algorithm for clean heating temperature based on optical fiber grating temperature sensors

This paper proposes an intelligent control algorithm based on fiber Bragg grating temperature sensors to address the problems of inaccurate temperature measurement caused by electromagnetic interference in traditional temperature sensors in geothermal clean heating systems, poor adaptability of conventional PID controllers to complex and variable working conditions, and large control overshoot. This algorithm uses fiber Bragg grating sensors to construct a time-division multiplexing sensing network, which utilizes its anti-electromagnetic interference characteristics and the linear relationship between temperature and wavelength to solve the problem of accurate temperature measurement in complex geothermal heating environments, providing real-time and reliable data for temperature control. In terms of control indicators, time squared multiplied by absolute error integral is used instead of traditional absolute error integral to adapt to conditions with variable parameters. At the same time, the back propagation neural network is introduced to perform online adaptive tuning of the proportional, integral, and derivative parameters of the PID controller, enabling the controller to automatically adjust control parameters based on the real-time operating status of the system, and improve its response capability to complex working conditions such as sudden changes in thermal load and outdoor temperature. The experimental results show that under high interference levels, the sensor network can still stably transmit 20 data packets within 100 s. Compared with existing methods based on wireless temperature sensors, thermocouple sensors, and model predictive control, the control overshoot of this algorithm is reduced to 8%, and the adjustment time is shortened to 10.2 min. During the 24-h continuous operation test, when the outdoor temperature fluctuated within the range of 5–12 °C, the indoor temperature remained stable at around 25 °C without any noticeable fluctuations. This algorithm provides a temperature control scheme for geothermal clean heating with anti-interference ability, adaptive adjustment ability, and high-precision control performance.