Data-Driven Control of DC-DC Boost Converters Interfaced with Constant Power Loads

Abstract

This paper presents a data-driven control framework to improve the stability and optimize the performance of DC-DC boost converters supplying constant power loads (CPLs). The inherent negative impedance and non-linear characteristics of CPLs pose significant stability challenges in power electronic systems. To address these issues, this study evaluates the performance of data-driven integrator (I) and linear quadratic integral (LQI) controllers, both optimized using iterative feedback tuning (IFT), that eliminates the need for an explicit system model. The proposed controllers are systematically compared against conventional model-based designs to assess their effectiveness. Key dynamic challenges, including converter non-linearity, CPLinduced instability, and measurement noise, are considered in the analysis. Simulation results demonstrate that the data-driven LQI and I controllers achieve superior tracking accuracy, robustness, and stability. These findings underscore the advantages of datadriven control methodologies in ensuring reliable and efficient operation in practical power electronic applications.