Design of Cardiac Pacemaker Controller Based on Reinforcement Learning

This study investigates the derivation of PID controller parameters, commonly used for pacemaker control, using both genetic algorithm (GA) and reinforcement learning (RL) methods. We compare the PID parameters obtained by RL with those obtained by GA, a well-known and often preferred method in the literature. The aim of the study is to analyze the performance of the control parameters obtained by both methods and to determine which approach is more effective in pacemaker applications. In particular, comparisons on important control criteria such as rise time, settling time and overshoot of the system will reveal the advantages and disadvantages of these methods.