Hybrid strategy based model parameter estimation of irregular-shaped underwater vehicles for predicting velocity

Abstract The hydrodynamic model can be used to predict velocity of underwater vehicles in still water. However, there are few economical and effective methods for estimating the hydrodynamic parameters of irregular-shaped underwater vehicles. Thus, this paper proposes a hybrid estimation strategy, which contains a rough estimation using a least squares (LS) based algorithm and a precise estimation using an improved particle swarm optimization (IPSO) algorithm. The numerical simulation and field data based tests suggest that the accuracy of the predicted velocity using the hydrodynamic parameters estimated by the IPSO-based hybrid strategy is better than two state-of-the-art algorithms. Finally, a pool experiment is conducted to verify the accuracy of the predicted horizontal velocity of the underwater vehicle.

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