Affiliation:
1. School of Information Engineering, Shanghai Maritime University, Shanghai 201308, China
Abstract
Over the past few decades, unmanned surface vehicles (USV) have drawn a lot of attention. But because of the wind, waves, currents, and other sporadic disturbances, it is challenging to understand and collect correct data about USV dynamics. In this paper, the Modified backpropagation neural network (BPNN) is suggested to address this issue. The experiment was conducted in the Qinghuai River, and the receiver collected the data. The modified BPNN outperforms the conventional BPNN in terms of ship trajectory forecasting and the rate of convergence. The updated BPNN can accurately predict the rotational velocity during the propeller’s acceleration and stability stages at various rpms.
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