Survival strategies for unmanned surface vehicles in harsh ocean environments

Li, Zhi (2018) Survival strategies for unmanned surface vehicles in harsh ocean environments. Doctoral (PhD) thesis, Memorial University of Newfoundland.

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Unmanned Surface Vehicles (USVs) have seen fast development in the past decades, and they have opened up new ways for observing the ocean. A USV can run autonomous missions on the water surface with different payload sensors for characterizing the chemical and physical properties of the water column. With a group of USVs operated simultaneously in a fleet, the ocean observation work can be extended to much larger areas to achieve diverse scientific objectives. The ocean has very challenging environments, and to enable a USV to successfully complete each survey mission under adverse weather conditions, it is of great importance to investigate accurate and robust path-following control algorithms. Further, the unexpected ocean disturbances on a USV can potentially lead to critical motions, which may cause a USV to capsize. Therefore, the safety analysis of a USV that runs a mission in the seaway becomes a particularly important subject. This thesis provides a comprehensive investigation into the operation of a USV executing autonomous missions in adverse ocean environments. We investigate a USV’s dynamic motion modeling and validation in 6 degrees of freedom (DOF), examine three path-following control algorithms and their real-world performance in adverse weather conditions, as well as establish the safe operational condition for a USV that operates in dynamic ocean environments. We hope that our accomplished work can assist the USV practitioners in choosing appropriate motion dynamics models and robust path-following control strategies, and potentially implementing our safety analysis results to improve a USV’s operational safety and survivability during its ocean exploration mission. The planar motion dynamics are derived from the 6 DOF rigid-body motion equations, based on which a hybrid identification method that combines the tow tank and field tests has been carried out to determine the model parameter values. Depending on the constructed planar dynamic motion model, we develop and test three path-following control algorithms, i.e. Vector Field Method (VF), Carrot Chasing Method (CC) and Line-of-Sight Method (LOS). Our investigation involves investigating their mathematical origins, performing simulation tests and carrying out field experiments in adverse weather conditions to examine each algorithm’s robustness. Understanding the uncontrollable oscillatory motions in heave, roll and pitch are critical for the safety of a USV that operates in harsh ocean environments. The major influence on a USV’s oscillatory motion comes from the ocean waves. Since this highly nonlinear interactive dynamics are quite complicated, we implement three mathematical tools for the safety analysis, which includes the Analytical Method, Melnikov’s Method and Erosion Basin Method. Using the approximated analytical solution, we demonstrate the wellknown jump phenomenon for the nonlinear oscillatory motion. Using Melnikov’s function, we determine a conservative critical condition to predict the occurrence of chaotic motion, which can be regarded as a USV’s safe operation boundary condition. The erosion basin numerical analysis has been implemented as a supplement for the Melnikov’s method, and the results show that the achieved Melnikov boundary condition corresponds to the 90% safe region proportion contour. The boundary condition has been successfully combined together with the wave excitation moments to determine the safe and unsafe operational regions for a USV. These results are summarized in a series of unsafe region contour plots in the 2D polar coordinates.

Item Type: Thesis (Doctoral (PhD))
Item ID: 13042
Additional Information: Includes bibliographical references (pages 234-241).
Keywords: Unmanned Surface Vehicle, Path-Following Control, Dynamic System Modeling, Safety Analysis
Department(s): Engineering and Applied Science, Faculty of
Date: May 2018
Date Type: Submission
Library of Congress Subject Heading: Vehicles, Remotely piloted--Testing; Marine engineering.

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