Design and Noise Reduction for Fuzzy Proportional-Integral-Derivative Logic Controller Using Kalman Filter

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.