Hydrodynamic coefficients identification of pitch and heave using multi-objective evolutionary algorithm

The parameters of ship heave and pitch motions obtained by system identification is a popular approach in recent years. However, the single-objective optimization algorithm can only get one group of parameters, and these parameters are usually fail to achieve the optimal state of the heave and pitch motions simultaneously. To address this situation, we develop a multi-objective strategy to identify the parameters of pitch and heave coupled motions. We discuss the mathematical models for heave and pitch coupled motions and the unknown parameters in these equations are then identified using NSGA II, MOEA/D and MOPSO approaches. Firstly, the forming filters are modeled for the wave disturb and the wave force of heave and moment of pitch are simulated, and then the multi-objective functions and constrained conditions are designed and a decision maker are used to help the customer to select the proper parameters. At last, simulation result shows that the decision maker can choose the appropriate hydrodynamic parameter according to their prefer. The heave and pitch motions are agreement with the test data from the pool experiment under sea state 5, but the fitting accuracy of the sea state 3 needs to be further improved. © 2018 Elsevier Ltd