Application of Real-Coded Genetic Algorithm–PID Cascade Speed Controller to Marine Gas Turbine Engine Based on Sensitivity Function Analysis

Yunhyung Lee, Kitak Ryu, Gunbaek So, Jaesung Kwon and Jongkap Ahn ()
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Yunhyung Lee: Ocean Technology Training Team, Korea Institute of Maritime and Fisheries Technology, Busan 49111, Republic of Korea
Kitak Ryu: Ocean Technology Training Team, Korea Institute of Maritime and Fisheries Technology, Busan 49111, Republic of Korea
Gunbaek So: Department of Maritime Industry Convergence, Mokpo National Maritime University, Mokpo-si 58628, Republic of Korea
Jaesung Kwon: Department of Mechanical System Engineering, Gyeongsang National University, Tongyeong-si 53064, Republic of Korea
Jongkap Ahn: Training Ship Operation Center, Gyeongsang National University, Tongyeong-si 53064, Republic of Korea

Mathematics, 2025, vol. 13, issue 2, 1-19

Abstract: 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 M s (maximum sensitivity) values and minimal changes in M s 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.

Keywords: gas turbine engine; COGAG; genetic algorithm; maximum sensitivity (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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