Gas turbine engines at sea, characterized by nonlinear behavior and parameter variations due to dynamic marine environments, pose challenges for precise speed control. The focus of this study was a COGAG system with four LM-2500 gas turbines. A third-order model with time delay was derived at three operating points using commissioning data to capture the engines’ inherent characteristics. The cascade controller design employs a real-coded genetic algorithm–PID (R-PID) controller, optimizing PID parameters for each model. Simulations revealed that the R-PID controllers, optimized for robustness, show Nyquist path stability, maintaining the furthest distance from the critical point (−1, j0). The smallest sensitivity function $Ms$ (maximum sensitivity) values and minimal changes in $Ms$ for uncertain plants confirm robustness against uncertainties. Comparing transient responses, the R-PID controller outperforms traditional methods like IMC and Sadeghi in total variation in control input, settling time, overshoot, and ITAE, despite a slightly slower rise time. However, controllers designed for specific operating points show decreased performance when applied beyond those points, with increased rise time, settling time, and overshoot, highlighting the need for operating-point-specific designs to ensure optimal performance. This research underscores the importance of tailored controller design for effective gas turbine engine management in marine applications.

Ground fault detection in DC-links of high-voltage AC drives is challenging because faults may not produce large currents, while neutral-point voltage monitoring can lose sensitivity under nearly balanced pole-to-ground conductances. This paper develops a physics-based mathematical model and a multipath detection framework for the 5 kV DC-link of the GE MV7306 drive. A closed-form expression for the neutral-point voltage $V_{DC0}$ is derived using Kirchhoff’s current law in terms of equivalent pole-to-ground conductances. A normalized conductance asymmetry index characterizes near-balanced conditions, and logarithmic resistance sensitivity identifies the characteristic transition, $G_{fault}=G_{ref}$, beyond which the neutral-point voltage approaches saturation. The analytical model is also used to relate the fixed voltage threshold to the corresponding fault conductance and fault resistance boundaries. A multipath architecture combining fixed-threshold and robust adaptive-threshold paths is then developed. Circuit-model-based simulations consider degradation–recovery, variable-resistance surface leakage, and near-symmetric conductance oscillation scenarios. The proposed method detects all three scenarios with delays of 1.213, 0.031, and 0.141 s, respectively. For the two scenarios detected by both the proposed method and the fixed-threshold baseline, the mean detection delay decreased from 0.822 to 0.622 s, a 24.3% reduction. The results establish a direct link between the conductance model, nonlinear sensitivity characteristics, and multipath ground fault detection.