Autonomous Underwater Vehicle Control

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.