The lungs are particularly vulnerable to acute, critical illness. Respiratory failure can result not only from primary lung pathology, such as pneumonia, but also as a secondary consequence of heart failure or inflammatory illness, such as sepsis or trauma. When this occurs, it is essential to support patients with mechanical ventilation while the fundamental disease process is addressed. The goal of mechanical ventilation is to ensure adequate ventilation, which involves a magnitude of gas exchange that leads to the desired blood level of carbon dioxide, and adequate oxygenation that ensures organ function. Achieving these goals is complicated by the fact that mechanical ventilation can actually cause acute lung injury, either by inflating the lungs to excessive volumes or by using excessive pressures to inflate the lungs. Thus, the challenge to mechanical ventilation is to produce the desired blood levels of carbon dioxide and oxygen without causing further acute lung injury. In this research, we develop an analysis and control synthesis framework for a pressure-limited respirator and lung mechanics system using compartment models. Specifically, a general mathematical model is developed for the dynamic behavior of a multicompartment respiratory system. Then, based on this multicompartment model, an optimal respiratory pattern is characterized using classical calculus of variations minimization techniques for inspiratory and expiratory breathing cycles. Furthermore, model predictive controller frameworks are designed to track the given optimal respiratory air flow pattern while satisfying control input amplitude and rate constrains.

For elderly Canadians, the prevalence of vision impairment caused by degenerative retinal pathologies, such as age-related macular degeneration and retinitis pigmentosa, is at an occurrence rate of 14 percent, and on the rise. It has been shown that visual function can be restored by electrically stimulating intact retinal tissue with an array of micro-electrodes with suitable signals. Commercial retinal implants carrying such a micro-electrode array achieve this, but to date must receive power and data over copper wire cable passing through a permanent surgical incision in the eye wall (sclera). This project is defined by a collaboration with iBIONICS, who are developing retinal implants for treatment of such conditions. iBIONICS has developed the Diamond Eye retinal implant, along with several technology sub-systems to form a comprehensive and viable medical solution. Notably, the Diamond Eye system can be powered wirelessly, with no need for a permanent surgical incision. The thesis work is focused on the formulation, simulation and hardware demonstration of a powering system, mounted on glasses frame, for a retinal implant. The system includes a Micro-Electro-Mechanical System (MEMS) mirror that directs a laser beam to the implant through the pupil opening. The work presented here is built on two main components: an iterative predictor-corrector algorithm (Kalman filter) that estimates pupil coordinates from measurements provided by an image-based eye tracking algorithm; and an misalignment compensation algorithm that maps eye pupil coordinates into mirror coordinates, and compensates for misalignment caused by rigid body motions of the glasses lens mirror and the MEMS mirror with respect to the eye. Pupil tracker and misalignment compensation control performance are illustrated through simulated scenarios. The project also involves the development of a hardware prototype that is used to test algorithms and related software.