Novel Intelligent Control System for Combating Ventilator Induced Lung Injury
Jason Andrew Cahill
Mechanical ventilation, as a resource for critical care, is a balancing act. Every day physicians, nurses, and respiratory therapists rely on this life saving intervention to support patients who are too weak or ill to breathe on their own. Unfortunately, structural and physiological damage can easily occur as a result of aggressive or long-term ventilator use. Because of the cardiopulmonary system’s tremendous complexity as well as the innate variability in parameters due to disease, individuality, and time, most ventilators require continual adjustment to avoid these side effects, essentially making the physician the controller. This project proposes a radical step forwardin design, a three-part control method that will bring the patient into the loop in an unprecedented way. First, a nonlinear controller utilizing a generic model of the cardiopulmonary system. Second, a neural network-based adaptive controller capable of reducing the immediate deviation between the first controller and the real patient. Finally, an intelligent system identification algorithm that optimizes the parameters of the first controller in real-time, thereby further reducing error associated with long term variations. At each step the controller will be analyzed, developed, and tested via simulation, with the final product signifying a leap forward in respiratory care.
Raul E. Ordonez
Primary Advisor's Department
Electrical and Computer Engineering
Stander Symposium project, School of Engineering
United Nations Sustainable Development Goals
Good Health and Well-Being
"Novel Intelligent Control System for Combating Ventilator Induced Lung Injury" (2020). Stander Symposium Projects. 1846.