Next-Generation Modulation and Control of Power Electronic Systems: AI-Enabled Control, Digital Twins, Fault-Tolerant Operation, and Cyber-Physical Security

Power electronic systems are evolving from conventional fixed-function converters toward intelligent, adaptive, and cyber-physical energy-conversion platforms in which modulation, predictive control, artificial intelligence (AI), digital twins (DTs), fault diagnosis, and cybersecurity increasingly interact within a unified closed-loop architecture. This paper presents an integrated review and mathematical framework for next-generation modulation and control of power electronic systems, with an emphasis on advanced modulation, predictive control, AI-assisted adaptation, converter-oriented digital state estimation, fault-tolerant operation, and cyber-resilient control. The proposed framework links converter dynamics, state and parameter estimation, physical faults, cyber disturbances, supervisory anomaly assessment, and mode-dependent control reconfiguration. Two clearly separated validation levels complement the literature synthesis: experimentally measured operating data are used to establish physically representative operating conditions, whereas a dedicated converter-control model is used to evaluate closed-loop dynamic resilience. Under a combined physical/cyber disturbance, resilient reconfiguration reduced the post-event speed RMSE from 9.203 to 0.425 rad/s, the peak speed error from 29.999 to 1.724 rad/s, and the maximum current from 69.112 to 10.662 A, while eliminating 829 current-constraint violations observed without resilience. Across 100 randomized Monte Carlo trials, the mean post-event RMSE decreased from 11.951 ± 3.060 to 0.769 ± 0.291 rad/s, with the corresponding 95% confidence interval narrowing from 11.351–12.550 to 0.712–0.826 rad/s. The results provide simulation-based, closed-loop evidence that coordinated state estimation, anomaly assessment, and resilient reconfiguration can substantially limit disturbance propagation while maintaining converter-control performance under combined physical and cyber abnormalities. Hardware-in-the-loop and embedded real-time implementation remain subjects for future validation.