No description available.

A cooperative project between the Universities of Plymouth and Cranfield was aimed at designing and developing an autonomous underwater vehicle named Hammerhead. The work presented herein is to formulate an advance guidance and control system and to implement it in the Hammerhead. This involves the description of Hammerhead hardware from a control system perspective. In addition to the control system, an intelligent navigation scheme and a state of the art vision system is also developed. However, the development of these submodules is out of the scope of this thesis. To model an underwater vehicle, the traditional way is to acquire painstaking mathematical models based on laws of physics and then simplify and linearise the models to some operating point. One of the principal novelties of this research is the use of system identification techniques on actual vehicle data obtained from full scale in water experiments. Two new guidance mechanisms have also been formulated for cruising type vehicles. The first is a modification of the proportional navigation guidance for missiles whilst the other is a hybrid law which is a combination of several guidance strategies employed during different phases of the flight. In addition to the modelling process and guidance systems, a number of robust control methodologies have been conceived for Hammerhead. A discrete time linear quadratic Gaussian with loop transfer recovery based autopilot is formulated and integrated with the conventional and more advance guidance laws proposed. A model predictive controller (MPC) has also been devised which is constructed using artificial intelligence techniques such as genetic algorithms (CA) and fuzzy logic. A CA is employed as an online optimization routine whilst fuzzy logic has been exploited as an objective function in an MPC framework. The CA-MPC autopilot has been implemented in Hammerhead in real time and results demonstrate excellent robustness despite the presence of disturbances and ever present modelling uncertainty. To the author's knowledge, this is the first successful application of a CA in real time optimization for controller tuning in the marine sector and thus the thesis makes an extremely novel and useful contribution to control system design in general. The controllers are also integrated with the proposed guidance laws and is also considered to be an invaluable contribution to knowledge. Moreover, the autopilots are used in conjunction with a vision based altitude information sensor and simulation results demonstrate the efficacy of the controllers to cope with uncertain altitude demands.

In moderate sea states, the predictions of the wave drift forces based on the potential theory correlate well with measurements. However, in severe wave conditions model tests have shown that there is an increase in wave drift forces as the sea states increases. Such difference is explained by the viscous drift forces acting in the waterline zone of a structure. This thesis presents an experimental study of the low-frequency surge motion loading on and response of a semisubmersible model in different sea states ranging between moderate and extreme. In addition to the experimental study, the thesis includes numerical simulations. The experimental tests were conducted in MARINTEK ocean basin with a 1/50 scale model which was moored using horizontal springs and catenary mooring lines. The environmental conditions included waves, current and combined wave and current fields. The waves used included both regular and irregular waves. In addition, decay tests were conducted in still water and in current. For irregular waves, statistical analysis of the values of mean value and standard deviation of the motion responses was carried out to investigate the effect of wave-current interaction and different sea states on these values. As for the numerical simulations, a mathematical model that is based on Morison's approach was used to predict the dynamic surge motion loading on and responses of a semisubmersible platform. In addition, the steady and slowly varying wave forces are predicted using Pinkster's procedure. The second numerical simulation was carried out using three-dimensional diffraction program that estimates the six degrees of freedom loading and responses in regular waves with and without the viscous damping effects. The damping of the system stems from both the hull and the mooring system. The mooring system damping was studied using the energy dissipation method to estimate the damping of the mooring line using the amplitude of the surge motion of the vessel.

No description available.

The work in this thesis concerns with the development of a novel multisensor data fusion (MSDF) technique, which combines synergistically Kalman filtering, fuzzy logic and genetic algorithm approaches, aimed to enhance the accuracy of an autonomous underwater vehicle (AUV) navigation system, formed by an integration of global positioning system and inertial navigation system (GPS/INS). The Kalman filter has been a popular method for integrating the data produced by the GPS and INS to provide optimal estimates of AUVs position and attitude. In this thesis, a sequential use of a linear Kalman filter and extended Kalman filter is proposed. The former is used to fuse the data from a variety of INS sensors whose output is used as an input to the later where integration with GPS data takes place. The use of an adaptation scheme based on fuzzy logic approaches to cope with the divergence problem caused by the insufficiently known a priori filter statistics is also explored. The choice of fuzzy membership functions for the adaptation scheme is first carried out using a heuristic approach. Single objective and multiobjective genetic algorithm techniques are then used to optimize the parameters of the membership functions with respect to a certain performance criteria in order to improve the overall accuracy of the integrated navigation system. Results are presented that show that the proposed algorithms can provide a significant improvement in the overall navigation performance of an autonomous underwater vehicle navigation. The proposed technique is known to be the first method used in relation to AUV navigation technology and is thus considered as a major contribution thereof.

The work in this thesis is concerned with the development of a novel and practical collision avoidance system for autonomous underwater vehicles (AUVs). Synergistically, advanced stochastic motion planning methods, dynamics quantisation approaches, multivariable tracking controller designs, sonar data processing and workspace representation, are combined to enhance significantly the survivability of modern AUVs. The recent proliferation of autonomous AUV deployments for various missions such as seafloor surveying, scientific data gathering and mine hunting has demanded a substantial increase in vehicle autonomy. One matching requirement of such missions is to allow all the AUV to navigate safely in a dynamic and unstructured environment. Therefore, it is vital that a robust and effective collision avoidance system should be forthcoming in order to preserve the structural integrity of the vehicle whilst simultaneously increasing its autonomy. This thesis not only provides a holistic framework but also an arsenal of computational techniques in the design of a collision avoidance system for AUVs. The design of an obstacle avoidance system is first addressed. The core paradigm is the application of the Rapidly-exploring Random Tree (RRT) algorithm and the newly developed version for use as a motion planning tool. Later, this technique is merged with the Manoeuvre Automaton (MA) representation to address the inherent disadvantages of the RRT. A novel multi-node version which can also address time varying final state is suggested. Clearly, the reference trajectory generated by the aforementioned embedded planner must be tracked. Hence, the feasibility of employing the linear quadratic regulator (LQG) and the nonlinear kinematic based state-dependent Ricatti equation (SDRE) controller as trajectory trackers are explored. The obstacle detection module, which comprises of sonar processing and workspace representation submodules, is developed and tested on actual sonar data acquired in a sea-trial via a prototype forward looking sonar (AT500). The sonar processing techniques applied are fundamentally derived from the image processing perspective. Likewise, a novel occupancy grid using nonlinear function is proposed for the workspace representation of the AUV. Results are presented that demonstrate the ability of an AUV to navigate a complex environment. To the author's knowledge, it is the first time the above newly developed methodologies have been applied to an A UV collision avoidance system, and, therefore, it is considered that the work constitutes a contribution of knowledge in this area of work.

The ‘Zero-G’ is designated as a new class of underwater robot that is capable of unrestricted attitude control. A novel control scheme based on internal actuation using Control Moment Gyros (CMGs) is proposed to provide Zero-G Class Autonomous Underwater Vehicles (AUVs) with this unique freedom in control. The equations of motion for a CMG actuated underwater robot are derived and a nonlinear feedback control law formulated based on energy considerations of the system’s coupled dynamics. Singularities, redundancy and null motion are discussed in the context of CMGs and a mathematical escapability condition is developed based on the differential geometry of null motion. A comprehensive geometric study of the singularities of a CMG pyramid is performed and together with considerations of the inverse kinematics of attitude control form the basis of a global steering law that exactly achieves the desired torques, whilst guaranteeing real-time singularity avoidance within a constrained workspace. The development of the CMG actuated Zero-G Class underwater robot IKURA is described. This is the first Zero-G Class prototype and is the first application of CMGs to underwater robots. A series of experiments to demonstrate the practical application of CMGs and verify the associated theoretical developments is described. The open-loop dynamics of the system and the exactness and real-time applicability of the CMG steering law are verified. Experiments are carried out to assess the performance of the proposed control law by comparing the response of the robot to that using alternative control laws that neglect the hydrodynamic interactions of the body and the coupled motion of the CMGs and body respectively. The control law demonstrates a faster response with a smaller overshoot for less overall control activity than the alternative methods. The ability to actively stabilise the passively unstable translational dynamics of the robot are verified. Next, the unrestricted attitude control capability is confirmed with the robot demonstrating the necessary range of attitude control to adopt and maintain any attitude on the surface of a sphere. Finally, the ability to stabilise any attitude while translating in surge is confirmed with the robot performing vertically pitched diving and surfacing in surge. This is the first time an underwater robot has performed such a manoeuvre. This research demonstrates that CMGs are capable of actively stabilising the passively unstable dynamics of an underwater robot with essentially zero-righting moment and are capable of providing it with unrestricted attitude control. The three-dimensional manoeuvring capabilities allow Zero-G Class underwater robots to plan and optimise their missions in a fully threedimensional manner, in a way that has not been possible previously. This study concludes that the application of CMGs for attitude control opens up a path to develop sophisticated Zero-G Class underwater robots and their application to new fields of underwater research.