Study on the Improvement of Temperature Control System for Cabin Monitoring Device Based on Intelligent Fuzzy Control Algorithm

ObjectiveTo address the nonlinear, time-delayed, and highly disturbed challenges in environmental temperature control for cabin monitoring devices in engineering applications. Method An improved intelligent fuzzy control scheme integrating adaptive fuzzy PID, variable universe fuzzy control, and dual-mode switching is proposed. The scheme achieves rapid convergence for large deviations and precise locking for small deviations through a dual-mode switching mechanism. A variable universe scaling factor dynamically adjusts the input fuzzy universe to enhance resolution under all operating conditions, and its parameters are optimized by particle swarm optimization. A thermodynamic model of the cabin is established in MATLAB/Simulink for simulation, and hardware-in-the-loop tests are conducted to verify the real-time performance and resource occupancy of the algorithm. Results Simulation and comparative analysis show that compared with traditional PID control, the improved system reduces rise time by 23.2%, overshoot from 8.7% to less than 1%, steady-state error from ±0.53°C to ±0.18°C, and improves disturbance rejection by 48.5%. Hardware-in-the-loop tests on an STM32 platform indicate an execution cycle of 2.3ms and RAM usage of 4.2KB, meeting embedded deployment requirements. Conclusion The proposed integrated intelligent fuzzy control algorithm significantly outperforms traditional methods in control accuracy, response speed, and anti-interference capability, while requiring low computational resources and being easy to implement, offering a highly practical solution for intelligent temperature control in enclosed cabin monitoring environments.