Abstract
Using the traditional PID controller, it can reduce the amount of fuel, decrease the emission of pollutants and can improve the efficiency of the marine diesel engines. Therefore, it is mostly used in the electronic governor of the marine diesel engine's speed control system. However, as the change of sea conditions, the non-linear of the diesel and the change of the load, the parameters of the system model would change immediately. It is required that the controller's parameters can be adjusted on line. In this paper, using the large-scale low-speed two-stroke marine diesel engine of a real ship as the simulation object, the self-turning PID controller based on BP neural network is designed. The simulation results show that it can achieve better control performance.
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