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Wave energy converters (WECs) exploit ocean wave energy and convert it into useful forms such as electricity. But for WECs to be successful on a large scale, two primary conditions need to be satisfied. The energy generated must satisfy the network requirements, and second, energy flow from waves to the grid needs to be maximized. In this dissertation, we address the second problem. Most control techniques for WECs today use the Cummins' linear model to simulate WEC hydrodynamics. However, it has been shown that under the application of a control force, where WEC motions are amplified, the linear model diverges from actual motions. Hence, it becomes necessary to model the nonlinear motion for realistic energy capture prediction. In this work, it is shown that a closed form energy optimal solution to the nonlinear model requires satisfaction of initial conditions that violate physical restrictions. Numerical optimization based controllers that use physical constraints as a necessary condition require large computation costs and are difficult to implement in real time. To mitigate computation costs for real-time implementation while precisely predicting nonlinear behavior, an efficient method of modelling WECs using an estimated linear model for computing the energy optimal control solution is presented. The estimated linear model is compared against the Cummins' model for accuracy of motion during an uncontrolled case. It is also shown that, there exists a force which results in higher energy extraction than optimal force from Cummins' model when applied to a xxi nonlinear model. Additional analyses are also performed to evaluate the robustness of the proposed method in random and extreme sea states.

CLOSED LOOP ENERGY MAXIMIZING CONTROL OF A WAVE ENERGY CONVERTER USING AN ESTIMATED LINEAR MODEL THAT APPROXIMATES THE NONLINEAR FROUDE-KRYLOV FORCE