A hybrid-driven underwater glider model, hydrodynamics estimation, and an analysis of the motion control
A hybrid-driven underwater glider model, hydrodynamics estimation, and an analysis of the motion control
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DOI：
10.1016/j.oceaneng.2014.02.002
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发表时间：
2014-05-01
影响因子：
5
通讯作者：
Ishak, Syafizal
中科院分区：
文献类型：
--
作者：
Isa, Khalid;Arshad, M. R.;Ishak, Syafizal
自主混合驱动滑翔机是一种新型的自主水下滑翔机，它集成了浮力驱动水下滑翔机和传统自主水下滑翔机的概念。水下机器人（AUV）这种滑翔机具有多功能，使其能够克服浮力驱动滑翔机的速度和机动性限制。因此，本文提出了混合驱动滑翔机的数学模型，估计的流体动力学和运动控制的分析。一个牛顿的方法已被用来模拟滑翔机的影响下的水流。此外，流体动力学估计，通过使用切片理论和计算流体动力学（CFD）。为了分析滑翔机的运动，神经网络预测控制（NNPC）已被设计，并将其性能与模型预测控制（MPC）和线性二次型调节器（LQR）进行了比较。仿真结果表明，神经网络预测控制（NNPC）比MPC和LQR具有更好的控制性能。此外，计算结果还显示了滑翔机在速度、攻角和侧滑角下的水动力响应。(C)2014爱思唯尔有限公司版权所有。
An autonomous hybrid-driven glider is a new class of autonomous underwater glider that integrates the concept of a buoyancy-driven underwater glider and a conventional autonomous. underwater vehicle (AUV). This glider has multi-functionality that enables it to overcome the speed and maneuverability limitations of buoyancy-driven gliders. Thus, this paper presents a mathematical model of the hybrid-driven glider, an estimation of the hydrodynamics and an analysis of the motion control. A Newtonian approach has been used to model the glider under the influence of water current. In addition, the hydrodynamics were estimated by using a Strip theory and a computational fluid dynamic (CFD). In order to analyze the motion of the glider, a Neural Network Predictive Control (NNPC) has been designed and its performance has been compared with the Model Predictive Control (MPC) and Linear Quadratic Regulator (LQR). The simulation results demonstrated that the Neural Network Predictive Control (NNPC) produced better control performance than the performance of the MPC and LQR when dealing with disturbances. In addition, the results also demonstrate the hydrodynamic response of the glider over the velocity, angle of attack and sideslip angle. (C) 2014 Elsevier Ltd. All rights reserved.