Hybrid Sampled-Data Nonlinear Lyapunov Control with Variable Switching Frequency for DC–DC Buck Converters

Abstract

This paper presents a robust and adaptive control strategy for DC–DC buck converters that combines a nonlinear Lyapunov-based sampled-data framework with a variable switching frequency mechanism. The proposed controller is designed to operate in a digitally controlled environment, where discrete-time control laws directly interact with the continuous-time dynamics of the converter, reflecting the hybrid nature of modern power electronics systems. By employing Lyapunov stability theory in the discrete domain, global asymptotic stability is rigorously ensured, even in the presence of parameter uncertainties, external disturbances, and measurement noise. A key contribution of this work is the integration of a dynamic switching frequency scheme that modulates the pulse-width modulation frequency as a function of the sampled tracking error. This design enables high-frequency switching during large transients for fast and accurate regulation, while reducing the frequency under steady-state conditions to minimize switching losses and improve energy efficiency. The control input influences both the duty cycle and the switching period, achieving precise adaptation to changing load and reference conditions. Comprehensive simulation results conducted in MATLAB/Simulink validate the effectiveness of the proposed method. Compared to conventional fixed-frequency PID-based control, the nonlinear sampled-data controller demonstrates significantly faster transient response, reduced steady-state error, and superior robustness under load variations and noise injection. The results confirm the suitability of the proposed approach for high-performance digital power management systems, offering improved dynamic behavior and reduced switching activity without the need for gain retuning or model linearization.