Fuzzy-Immune Adaptive Fractional-Order LQI Control for Robust and Intelligent Heart Rate Regulation in Cardiac Pacemakers

Cardiac pacemakers are standard implantable medical devices that regulate and treat heart rhythm disorders, primarily aiming to improve patient health outcomes. This study presents the systematic design, implementation, and simulation-based validation of a novel fuzzy-immune adaptive Fractional-Order Linear Quadratic Integral (FO-LQI) control strategy for heart rate (HR) regulation using cardiac pacemakers. Unlike the conventional LQI controller, the proposed approach replaces the integer-order integrator with a fractional-order integral operator to enhance the controller’s design flexibility and dynamic response. To address the implementation challenges of fixed fractional exponents, a fuzzy-immune adaptation mechanism is introduced to modulate the fractional order in real time. This adaptive scheme improves the controller’s robustness across varying physiological states, enabling more responsive HR adaptation to the patient’s metabolic demands. The proposed controller is modeled and simulated in MATLAB/Simulink using physiologically relevant test cases. Comparative simulation results show that the fuzzy-immune adaptive FO-LQI controller outperforms the baseline LQI and fixed FO-LQI controllers in achieving time-optimal HR regulation. These findings validate the reliability and enhanced robustness of the proposed control scheme for simulating cardiac behavior under diverse physiological conditions.