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Dynamic analysis of raising sunken vessels using buoyant systems

In this research, mathematical formulations for the dynamics of raising sunken vessels using buoyant systems are developed in a form which is suitable for integrating control techniques to ensure both hydrodynamic and structural stability for a safe and stable salvaging operation based on both rigid body modeling and flexible body modeling concepts. Due to the coupled nature of salvage dynamics and for integrating controller techniques, the mathematical modeling is carried out as two subsystems. In the primary model, the salvage dynamics is formulated in such a way that the variation in additional buoyancy due to flow rate of filling gas inside the lift bags is the controlling force with respect to hydrostatic force due to weight, buoyancy and suction break out, hydrodynamic forces and uncertainty arises due to any external disturbances. In the secondary model, the purging of gas through the valves is taken as the control parameter by accounting the excess buoyancy available after suction break out and to the variation in pressure difference between gas inside lift bag and surrounding sea water pressure for a stable ascent. According to the simplified two-degree-of-freedom equations of rigid-body vessel motion, a state space model is developed for integrating the primary controller. Initially a proportional derivative (PD) controller is selected as the primary controller for regulating the flow rate of filling gas inside the lift bags according to the buoyancy requirement and extended to other classic controllers like proportional integral and derivative (PID) controller and sliding mode controller (SMC) for improving the performance. Numerical simulations are carried out in MATLAB & SIMULINK by solving the standard State Dependent Ricatti Equation in a body-fixed coordinate reference frame. Preliminary results in terms of coordinate positions or trajectories, linear and angular velocity components of the raising body are evaluated based on an experimental pontoon model. A number of case studies are carried out for different target depths with the developed linear state space model including sensitivity analysis such as change in hydrodynamic coefficients, breakout lift force and the effect of external disturbances and uncertainty. SMC is found to be the optimum choice among these conventional controllers by satisfying the Lyapunov stability condition even for higher water depths with system robustness and capability to handle parameter variations, external disturbances and uncertainty. The tuning effort and chattering were found to be the two major draw backs of conventional sliding mode controller (CSMC), which is improved by integrating it with artificial intelligence such as fuzzy logic controller to bring together the advantages of both controllers to become fuzzy sliding mode controllers (FSMCs). In FSMCs, the performance of the CSMC is improved by dynamically computing the sliding surface slope by a FLC and adaptively computing the controller gain by another FLC. FLCs are designed using MATLAB's fuzzy logic interface based on Mamdani's implification method the combined models will be developed in SIMULINK. A two input fuzzy sliding mode controller (TIFSMC) is designed first and later simplified to single input fuzzy sliding mode controller (SIFSMC), for reducing the tuning effort and computational time. With the development of SIFSMC, the tuning process becomes standardized and hassle free and hence the well known chattering problem associated with SMCs is avoided. The comparative performance of the fuzzy sliding mode controllers over CSMC has been investigated by performing numerical simulations on the pontoon model. It is found that both FSMCs show 30% of improvement in the tracking performance when compared to the CSMC, while maintaining its robustness. It is also noted that FSMCs are less sensitive to external disturbances and uncertainties in comparison with CSMC. The responses obtained by the SIFSMC are the same as those obtained by the TIFSMC, with the former involving a much less tuning effort and computational time. Simulation studies reveals the fact that for complicated non linear underwater operations like marine salvage involving uncertainty and external disturbances, a closed loop control system is mandatory and an adaptive controller like SIFSMC is the optimum choice as the primary controller for regulating the gas flow rate. Purge valve modeling is carried out according to the excess buoyancy available after suction breakout and to the variation in pressure difference between gas inside the lift bags and surrounding sea water for a stable ascent.
Date January 2014
CreatorsVelayudhan, Arun Kumar Devaki Bhavan
PublisherUniversity of Strathclyde
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation

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