International Journal of Fuzzy Logic and Intelligent Systems 2024; 24(3): 306-316
Published online September 25, 2024
https://doi.org/10.5391/IJFIS.2024.24.3.306
© The Korean Institute of Intelligent Systems
Tien Anh Tran1,2
1Faculty of Marine Engineering, Vietnam Maritime University, Haiphong, Vietnam
2Marine Research Institute, Vietnam Maritime University, Haiphong, Vietnam
Correspondence to :
Tien Anh Tran (trantienanhvimaru@gmail.com)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Controlling diesel engine speed is essential for stable and efficient ship operation. The diesel engine speed directly affects the fuel consumption of marine diesel engines. The choice of optimal engine speed is guided by extensive research in ship energy efficiency and diesel engine speed control theory. This study investigates the above issues by proposing a novel approach. The proposed method is more effective than traditional control methods. First, the traditional proportional-integral-derivative (PID) controller of marine diesel engine speed is established. Secondly, this controller adopts online tuning through fuzzy logic control theory using the Kalman filter method. Thereafter, a fuzzy logic controller and genetic algorithm are applied to tune the traditional PID controller. This study aims to obtain the optimal diesel engine speed controller with better dynamic and static performance than the traditional control methods. The results have been compared and verified with the equivalence fuzzy PID controller. The proposed controller is useful and significant in marine engineering, as it increases the stable and responded characteristics of marine diesel engine speed controllers.
Keywords: Marine diesel engine, Modern control theory, Genetic algorithm, Fuel oil consumption, Fuzzy PID control
No potential conflict of interest relevant to this article was reported.
International Journal of Fuzzy Logic and Intelligent Systems 2024; 24(3): 306-316
Published online September 25, 2024 https://doi.org/10.5391/IJFIS.2024.24.3.306
Copyright © The Korean Institute of Intelligent Systems.
Tien Anh Tran1,2
1Faculty of Marine Engineering, Vietnam Maritime University, Haiphong, Vietnam
2Marine Research Institute, Vietnam Maritime University, Haiphong, Vietnam
Correspondence to:Tien Anh Tran (trantienanhvimaru@gmail.com)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Controlling diesel engine speed is essential for stable and efficient ship operation. The diesel engine speed directly affects the fuel consumption of marine diesel engines. The choice of optimal engine speed is guided by extensive research in ship energy efficiency and diesel engine speed control theory. This study investigates the above issues by proposing a novel approach. The proposed method is more effective than traditional control methods. First, the traditional proportional-integral-derivative (PID) controller of marine diesel engine speed is established. Secondly, this controller adopts online tuning through fuzzy logic control theory using the Kalman filter method. Thereafter, a fuzzy logic controller and genetic algorithm are applied to tune the traditional PID controller. This study aims to obtain the optimal diesel engine speed controller with better dynamic and static performance than the traditional control methods. The results have been compared and verified with the equivalence fuzzy PID controller. The proposed controller is useful and significant in marine engineering, as it increases the stable and responded characteristics of marine diesel engine speed controllers.
Keywords: Marine diesel engine, Modern control theory, Genetic algorithm, Fuel oil consumption, Fuzzy PID control
Marine diesel engine speed control system.
Framework of marine diesel engine speed controller.
General scheme of a control system using state estimation.
Marine diesel engine speed controller using Kalman filter.
Control model of marine diesel engine speed.
Inference of the fuzzy logic controller.
Fuzzy logic control rule.
Surface simulation of output signals: (a) proportional gain (
Model of marine diesel engine speed controller in Simulink/MATLAB.
Equivalent PID logic controller on the Simulink platform.
Control signal .
Output signal.
Unit step signal.
Error derivative signal.
Trajectory between output gains and input. (a) Trajectory of
Zong Woo Geem, and Jin-Hong Kim
International Journal of Fuzzy Logic and Intelligent Systems 2018; 18(4): 237-244 https://doi.org/10.5391/IJFIS.2018.18.4.237Jae Ho Park, Jung Suk Yu, and Zong Woo Geem
Int. J. Fuzzy Log. Intell. Syst. 2018; 18(2): 135-145 https://doi.org/10.5391/IJFIS.2018.18.2.135Youngwan Cho, and Kisung Seo
Int. J. Fuzzy Log. Intell. Syst. 2018; 18(2): 111-119 https://doi.org/10.5391/IJFIS.2018.18.2.111Marine diesel engine speed control system.
|@|~(^,^)~|@|Framework of marine diesel engine speed controller.
|@|~(^,^)~|@|General scheme of a control system using state estimation.
|@|~(^,^)~|@|Marine diesel engine speed controller using Kalman filter.
|@|~(^,^)~|@|Control model of marine diesel engine speed.
|@|~(^,^)~|@|Inference of the fuzzy logic controller.
|@|~(^,^)~|@|Fuzzy logic control rule.
|@|~(^,^)~|@|Surface simulation of output signals: (a) proportional gain (
Model of marine diesel engine speed controller in Simulink/MATLAB.
|@|~(^,^)~|@|Equivalent PID logic controller on the Simulink platform.
|@|~(^,^)~|@|Control signal .
|@|~(^,^)~|@|Output signal.
|@|~(^,^)~|@|Unit step signal.
|@|~(^,^)~|@|Error derivative signal.
|@|~(^,^)~|@|Trajectory between output gains and input. (a) Trajectory of