摘要
呼吸机是一种精密机械通气装置,对控制系统的响应速度和控制精度有严格的要求。呼吸机的工作介质为压缩性极强的气体,导致该系统具有非线性和扰动强等特性,对于非线性系统传统PID控制器已经无法达到控制要求,基于PID控制的各种自适应算法得到了广泛研究,比如神经网络整定PID控制、遗传算法整定的PID控制、迭代学习PID控制等,但这些算法复杂度较大,对于实时性要求较高的系统难以实现。针对上述问题,以国内某公司试生产的一款气动比例阀为研究对象,通过对其进行力学分析并结合控制经验,建立了一套模糊PID控制规则,设计硬件电路并在STM32F767微控制器上编程实现了该算法,实验结果表明响应速度和控制精度均较好,输出流量有效范围7 L/min—180 L/min,稳态误差≤±4%,响应时间≤30 ms,输出流量稳定,系统鲁棒性较强,满足呼吸机应用要求。
Ventilator is a kind of mechanical ventilating device that has strict requirements on responding speed and control precision for the controlling system.Ventilator works with gas medium which is highly compressible,thus makes the system nonlinear and brings a lot of disturbance.Traditional PID controller is no longer able to satisfying the requirements for nonlinear system,a lot of adaptive algorithms based on PID control are developed widely,such as neural network tuning PID control,genetic algorithm tuning PID control,iterative learning PID control and so on,but considering real time controlling,these algorithms are too complicated to implement.To solve this problem,take a pneumatic proportional valve which is produced by a domestic company for trail as research object,analyze its mechanical structure and combine the controlling experiences,built a set of fuzzy PID control rule,designed hardware circuit and implemented this algorithm on STM32F767 microcontroller.Results show that both responding speed and control precision is satisfying,effective output flow ranged 7L/min to 180L/min,steady state error≤±4%,response time≤30ms,output flow is stable and the system is quite robust,can meet application requirement of ventilator.
作者
刘景康
龙飞
赵坤
张浩
LIU Jing-kang;LONG Fei;ZHAO Kun;ZHANG Hao(Beijing Key Laboratory of Communication and Radio Frequency IC Technology for Next Generation,Institute of Microelectronics,Chinese Academy of Sciences,Beijing 100029,China;Institute of Microelectronics,Chinese Academy of Sciences,Beijing 100029,China;University of Chinese Academy of Sciences,Beijing 100049,China)
出处
《电子设计工程》
2019年第2期94-99,共6页
Electronic Design Engineering
基金
湖北省中国科学院科技合作专项项目资助
