An optimization method for control parameters of underwater gliders considering energy consumption and motion accuracy
Abstract Energy consumption and motion accuracy are both important performance metrics for underwater gliders, which are closely related to the glider control parameters values. For the above two performance metrics, we study a multi objective optimization method to determine the control parameters values that make the glider have the better performance. Here the control parameters include the net buoyancy adjustment amount and the movable internal mass block translation amount. The basis of the optimization method is the dynamic model of the glider. Based on the dynamic model established by us, the evaluation parameter of energy utilization rate is deduced, and it reflects the ideal voyage range produced by 1 kJ energy. Besides, the evaluation parameter of motion accuracy is defined by the mean and standard deviation of the glider motion error in uncertain current. Next, the flow, which is used for calculating the above two evaluation parameters under the same set of control parameters values, is proposed. Based on the above flow and the radial basis function neural network, we fit surrogate models to participate in the optimization calculation to improve the efficiency. Here the optimization objectives are to maximize the energy utilization rate and minimize the glider motion error simultaneously. Then, we obtain the Pareto optimal set containing many sets of control parameters values by using the non dominated sorting genetic algorithm II. Finally, the selection rule of control parameters values is shown by an example. This research can be used for determining the appropriate control parameters values of underwater gliders in actual application.