A Control System for Automated Docking of an Unmanned Underwater Vehicle
Abstract: Unmanned underwater vehicles (UUV) are receiving increased attention for both military and civilian applications. For example, UUVs were deployed in the war against Iraq for mine counter measure missions and are becoming a necessary tool in the deep sea mining industry. If UUVs were able to dock while submerged, it would greatly increase their efficiency, as well as reduce the cost involved in their deployment and recovery. The ability to both operate and dock in a submerged state would also provide the UUV a degree of stealth. A future application where UUVs would prove a valuable asset is for harbor control where stealth is an essential quality. A submerged docking bay would enable the UUV to both upload completed mission data and download new mission objectives while recharging its batteries. To succeed in this endeavor, a control system capable of guiding the UUV safely into an underwater docking bay is required. This thesis describes the development of two different control algorithms, a fuzzy controller and a Linear Quadratic Regulator (LQR). For simulation purposes, a 3D model of a small UUV is generated using ADAMS/view software. Another model is generated in Simulink/MATLAB using the equations of motions for the UUV, yielding faster and more numerically stable simulations. Both models are including the effects of water drag and have vertical and horizontal rudders and thruster inputs. The controllers are built using Simulink/MATLAB and the simulations are run either using Simulink/MATLAB entirely or in co-simulation mode with ADAMS, enabling a more graphic representation of the results. The UUV chosen for this thesis is called REMUS and is developed by Woods Hole Oceanographic Institute. It measures 1.6 m and weighs 37 kg. Included in this work is a thorough analysis of both controllers including key results enabling a comparison of the two controllers performance. A number of requirements were set up for the controllers and except for water current disturbances, both controllers met their requirements. When off course the presented LQR is able to steer the UUV back on course more quickly and smoothly than the Fuzzy controller. The conclusion of this thesis when combining all characteristics of the different controllers’ performance is that the LQR is the natural choice of controller for autonomous underwater docking of an UUV. The research described in this thesis has the potential to further increase the efficiency of UUVs by enabling underwater docking. The ultimate future work would naturally be to test the described controllers on the REMUS in a test tank to verify the results presented in this thesis.
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