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Trajectory Tracking for Autonomous Underwater Vehicle Based on Model-Free Predictive Control

机译:基于无模型预测控制的自主水下航行器轨迹跟踪

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Model-free predictive control is a novel data-driven control approach. It can calculate directly the control input by using a great deal of input and output datasets. Moreover, compared with the conventional model predictive control, it does not need to construct a precise mathematical model. In this work, we propose the model-free predictive control to the motion control of the autonomous underwater vehicle(AUV). The nonlinear motion control problem of AUV is effectively solved and the proposed approach can enhance the performance of trajectory tracking for AUV. At last, we demonstrate the availability of this method by the numerical simulations of trajectory tracking.
机译:无模型预测控制是一种新颖的数据驱动控制方法。它可以使用大量输入和输出数据集直接计算控制输入。而且,与传统的模型预测控制相比,它不需要构建精确的数学模型。在这项工作中,我们将无模型预测控制提出给自主水下航行器(AUV)的运动控制。有效解决了AUV的非线性运动控制问题,所提方法可以提高AUV的轨迹跟踪性能。最后,通过轨迹跟踪的数值模拟证明了该方法的有效性。

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