Sliding Mode Adaptive Control for Proportional Solenoid Valves in Ventilators
Xiaosuo Luo, Xiufeng CaoIntroduction:
Proportional solenoid valves have been increasingly adopted in ventilators and life-support devices, where they enable precise regulation of air and oxygen flow rates when paired with flow sensors. Accurate flow output from proportional solenoid valves is critical for minimizing patient airway resistance. However, conventional control approaches suffer from insufficient accuracy, highlighting the need for improved strategies. This study aims to develop sliding mode adaptive algorithms for valve position control in proportional solenoid valves used in ventilators, thereby achieving high-precision flow rate regulation.
Methods:
The structural configuration and dynamic model of the valve are described. A differential sliding mode adaptive control algorithm is proposed. To address nonlinearities, uncertainties, and disturbances, an advanced quadratic sliding mode adaptive control algorithm is developed. The algorithms are validated through simulations, and the sliding mode adaptive algorithm is implemented for actual valve control.
Results:
Simulation results confirm the effectiveness of the proposed algorithms. In full-range practical tests, the developed sliding mode adaptive method significantly reduces flow delivery errors compared with fuzzy logic, feedforward-based PID, and model predictive control approaches.
Discussion:
The findings have significant implications for ventilator technology and clinical practice. By overcoming conventional limitations, the proposed algorithms enhance control accuracy and provide a reliable solution for improving ventilator performance. High-precision flow rate regulation can help optimize patient ventilation therapy, reduce complication risks from inaccurate delivery, and contribute to reliable life-support systems.
Conclusion:
The proposed proportional solenoid valve control method substantially improves ventilator control accuracy, providing technical support for advancing ventilator technology.