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Design of Tracking System and Disturbance Rejection Using Neural Networks for Autonomous Underwater Vehicle (AUV)

机译:基于神经网络的自主水下航行器(AUV)跟踪系统和干扰消除设计

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摘要

Autonomous Underwater Vehicle (AUV) is under-actuated system with highly nonlinear dynamic and Multi Input Multi Output (MIMO). AUV has stability problem due to external disturbance. These characteristics cause the AUV is difficult to be controlled and to track the reference signal automatically. Based on these problems, this paper present tracking control design and disturbance rejection using Neural Networks for AUV with 6 Degree of Freedom (DOF). The proposed control system is used to generate control signals to overcome the nonlinear dynamics of AUV. The reference signal is processed using Line of Sight (LOS) method to obtain the desired yaw of AUV. Simulation results show that the AUV is able to track the reference signal even in the presence of ocean current disturbance.
机译:自主水下航行器(AUV)是具有高度非线性动态和多输入多输出(MIMO)的欠驱动系统。由于外部干扰,AUV存在稳定性问题。这些特性导致AUV难以控制并且难以自动跟踪参考信号。基于这些问题,本文提出了基于神经网络的六自由度水下机器人的跟踪控制设计和干扰抑制方法。所提出的控制系统用于产生控制信号,以克服AUV的非线性动力学。使用视线(LOS)方法处理参考信号,以获得所需的AUV偏航。仿真结果表明,即使在洋流干扰的情况下,AUV也能够跟踪参考信号。

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