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.

Distributed secondary control achieves voltage restoration and power sharing through communication among adjacent units but exposes the microgrid to potential cyber-attacks. Traditional mitigation strategies modify the secondary controller after the attack, addressing the issue only postoccurrence. Furthermore, in microgrid planning, the structure of the communication network significantly influences the resilience to attacks, but it remains to be explored. This article presents a proactive defense mechanism by designing a resilient communication network. The proposed method quantifies the impact of attacks and develops a multiobjective optimization algorithm to design the network, considering quantified attacks, convergence, time-delay robustness, and communication costs. The method is validated through OPAL-RT simulations of an islanded microgrid with ten converters.