Autonomous Underwater Vehicle Control

M. Prasad
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Abstract

Earth, the third planet from the sun is the only planet on which life is known to exist. Seventy percent of the earth is covered by oceans. These oceans have been playing a very crucial role in transporting of goods even before the road. At the same time it cannot be ignored the possibilities of the negative role of the oceans- a very serious threat to human society and damage of man-made infrastructure through the natural phenomenon such as hurricanes and tsunamis, the latest being Hudhud in Visakhapatnam and Nilam in Chennai. Autonomous Underwater Vehicles (AUV) and Remotely Operated Vehicles (ROV), are considered as marine robots which are very useful for study of ocean resources such as aquaculture, offshore mining, ocean survey etc.,. This paper considers the dynamic modeling of an Autonomous Underwater Vehicle (AUV) which is used to track the AUV in the presence of ocean currents and other underwater environmental disturbances. Model Predictive Control (MPC) has been attempted on AUV for control purpose. The main advantage of using MPC is it can easily handle multi input multi output systems very effectively. Constraints on inputs, states and outputs can also be considered using this technique. It has the ability to handle model mismatch and disturbances. Sensor noise can be estimated using filter and Kalman filtering plays an important role in AUV navigation. AUV sensors play an important role in data collection and remote sensing. Global Positioning satellite (GPS) may not work in underwater environment for remote sensing. Inertial Measurement Unit (IMU) sensor is used to find position of a vehicle and it may also helpful for remote sensing. Mathematical modeling and MPC formulations are the contributions of this paper. The results presented in this paper can be summarized in three points as dynamic modeling of AUV, stability issues, and formulation of MPC. All the simulations are carried out in MATLAB environment. These results help to explain the AUV control concept which is essential for ocean studies to monitor the underwater environment.
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自主水下航行器控制
地球是距太阳第三远的行星,也是唯一已知有生命存在的行星。地球的百分之七十被海洋覆盖。这些海洋在货物运输中起着至关重要的作用,甚至比公路还早。与此同时,不能忽视海洋可能发挥的消极作用- -通过飓风和海啸等自然现象对人类社会构成非常严重的威胁,并破坏人造基础设施,最近的是维沙卡帕特南的哈德胡德和金奈的尼拉姆。自主水下航行器(AUV)和遥控航行器(ROV)被认为是海洋机器人,在水产养殖、近海采矿、海洋调查等海洋资源研究中非常有用。本文研究了自主水下航行器(AUV)的动力学建模问题,该问题用于在存在洋流和其他水下环境干扰的情况下对AUV进行跟踪。模型预测控制(MPC)已被尝试用于水下航行器的控制。使用MPC的主要优点是它可以很容易地处理多输入多输出系统。对输入、状态和输出的约束也可以使用这种技术来考虑。它具有处理模型不匹配和干扰的能力。传感器噪声可以通过滤波来估计,卡尔曼滤波在水下航行器导航中起着重要的作用。水下航行器传感器在数据采集和遥感中发挥着重要作用。全球定位卫星(GPS)可能无法在水下环境中进行遥感工作。惯性测量单元(IMU)传感器用于确定车辆的位置,也可用于遥感。数学建模和MPC公式是本文的贡献。本文的研究结果可以概括为水下航行器的动态建模、稳定性问题和MPC的制定三个方面。所有仿真均在MATLAB环境下进行。这些结果有助于解释在海洋研究中监测水下环境所必需的AUV控制概念。
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