Research on the temperature control of a cryogenic urine storage system based on improved adaptive LADRC

Routine urine tests play a vital role in the diagnosis of kidney and urinary system diseases, with test outcomes directly affecting disease diagnosis. However, if urine is exposed to room temperature for extended periods, it may lead to rapid degradation of the sample, thus affecting the accuracy of the test. Therefore, for urine that requires long-term storage for testing, it is necessary to control the temperature within an appropriate range during the collection process to effectively preserve the activity of urinary proteins and ensure the reliability of the test. To address this issue, a cryogenic urine storage system was developed, and a fuzzy LADRC temperature control algorithm combined with a Smith predictor was proposed, specifically designed for optimizing the temperature stability during urine collection and storage processes. Initially, the characteristics of the cryogenic storage system were analyzed. A simulation model combining the fuzzy LADRC with a Smith predictor was built using the MATLAB/Simulink simulation toolkit, and a comparative simulation was conducted. The simulation results showed that the proposed algorithm significantly improved the time-domain response performance compared to PID control, verifying the superiority of the algorithm over PID control. The final experimental results demonstrated that the fuzzy LADRC temperature control algorithm with the Smith predictor essentially eliminated overshoot, with improvements in speed and stability compared to PID control.