Applying the Bilinear Model to Identify the Ventilator’s Two Double-Acting Pistons Pump

The COVID-19 pandemic has had a comprehensive and far-reaching impact on various fields, especially medicine. Additionally, the pandemic has many generous of the COVID-19 virus that affects the economy, society, and human health. During the COVID-19 pandemic, medical equipment, especially ventilators, has seen a severe shortage. Thus, many studies of ventilators have been conducted around the world. In terms of the ventilator, flow control is one of the critical functions that is achieved for all ventilators. However, the flow control of the ventilator is only performed properly with the presence of known system parameters of a volume-controlled ventilator. This paper presents a model prediction of a volume-controlled ventilator through recorded data from experimental results. The main component of the ventilator is a two double-acting pistons pump driven by a brushless direct current (BLDC) motor to flow outgoing air. A bilinear model is employed to recognize the dynamic of the two double-acting pistons through sampled voltages supplied to the BLDC motor with respect to the sampled exhausting airflow. These sampled data are split into two sets. The former is used to identify the bilinear model, and the latter is treated as validation data. The identified bilinear model’s response has been validated and compared to the experimental result in terms of minimizing the mean squared error.