Acharya Debasis, Das Dushmanta Kumar
Department of Electrical and Electronics Engineering, National Institute of Technology Nagaland, India.
Department of Electrical and Electronics Engineering, National Institute of Technology Nagaland, India.
Comput Methods Programs Biomed. 2021 Jan;198:105776. doi: 10.1016/j.cmpb.2020.105776. Epub 2020 Oct 3.
An artificially ventilated human respiratory system is used to help breathing of a patient with respiratory problem. The level of oxygen is maintained stable by controlling the airway pressure in the lungs mechanism with the help of medical ventilator. For pressure control in a ventilator, the airway pressure in lungs mechanism is controlled by a motor driven piston mechanism. The optimal setting of controller parameters of a respiratory ventilator system depends on many factors of a patient such as physical condition of patient, need of oxygen, age of a patient etc. Therefore, computer operated algorithm based artificial ventilation system becomes most popular for its better performance, efficiency, and easy control mechanism. In this paper, a simple swarm optimization based controller design approach is systematically verified to design suitable controller for pressure controlled artificially ventilated human respiratory system. A modified constricted class topper optimization (C-CTO) algorithm is proposed for tuning the controller in an artificial ventilator system.
A pressure controlled ventilation (PCV) model has been considered. A proportional-integral-derivative (PID) controller structure is considered for the PCV. Three different optimization approach (Particle swarm optimization (PSO), class topper optimization (CTO) and a modified constricted class topper optimization (C-CTO)) are verified one by one for the purpose of tuning PID controller for PVC system.
The performances of swarm based controller in PCV system for three different cases are examined in terms of settling times and maximum overshoot of the system.
The swarm based optimization approach is improving the dynamic response of pressure control artificially ventilated human respiratory system. In this paper, a simple piston-motor driven lung mechanism is applied to verify the swarm based approach, but this approach can further be checked in the future for more complex human lungs artificially ventilated system.
人工通气的人体呼吸系统用于帮助有呼吸问题的患者呼吸。借助医用呼吸机，通过控制肺部气道压力机制来维持氧气水平稳定。对于呼吸机中的压力控制，肺部气道压力机制由电机驱动的活塞机构控制。呼吸通气系统控制器参数的最佳设置取决于患者的许多因素，如患者的身体状况、氧气需求、患者年龄等。因此，基于计算机操作算法的人工通气系统因其更好的性能、效率和易于控制的机制而变得最为流行。本文系统地验证了一种基于简单群体优化的控制器设计方法，以设计适用于压力控制的人工通气人体呼吸系统的控制器。提出了一种改进的压缩类顶尖优化（C-CTO）算法来调整人工通气系统中的控制器。
考虑了一种压力控制通气（PCV）模型。对于PCV，考虑了比例积分微分（PID）控制器结构。为了调整PVC系统的PID控制器，逐一验证了三种不同的优化方法（粒子群优化（PSO）、类顶尖优化（CTO）和改进的压缩类顶尖优化（C-CTO））。
根据系统的调节时间和最大超调量，研究了基于群体的控制器在PCV系统中三种不同情况下的性能。
基于群体的优化方法正在改善压力控制人工通气人体呼吸系统的动态响应。本文应用了一种简单的活塞-电机驱动的肺部机制来验证基于群体的方法，但未来可以进一步检查这种方法在更复杂的人工通气人体肺部系统中的情况。
