NEXT-GENERATION ARTIFICIAL HEART CONTROL : DEVELOPING AN INTELLIGENT CONTROL SYSTEM FOR OPTIMAL BLOOD FLOW AND PRESSURE IN A TOTAL ARTIFICIAL HEART

Abstract: Artificial hearts are an essential solution for patients suffering from end-stage heart failure. The precise control of these devices is critical for replicating the natural heart’s behavior and ensuring optimal patient health. This thesis presents the development and evaluation of control algorithms for a Total Artificial Heart (TAH). Our research initially considered the Proportional Integral Derivative (PID), Fuzzy-PID, and Artificial Neural Networks (ANN)-PID controllers. Through an iterative process of development and testing, two controllers emerged as the most effective: a Proportional (P) controller and a fuzzy Proportional Derivative (FPD) controller. These controllers were designed and simulated, followed by the generation of C code for implementation on an embedded system. An iterative approach was employed to design and test the controllers. First, the controllers were tested in a simulated environment, and then the validated designs were implemented and evaluated in a physical mock-loop system that mimicked the human circulatory system. The results demonstrated that both the P and FPD controllers were able to regulate the TAH operation. Notably, the FPD controller performs better based on the settling time, overshoot, and rise time in the simulation environment and stability in the physical environment. This thesis contributes to ongoing research in the field of TAH by providing a continuation that can advance the field’s development. These advancements could potentially improve the quality of life of patients awaiting heart transplants. Future work will include refining the FPD controller and conducting extensive physical testing and tuning.