Abstract
This paper investigates the application of a method to find the cost function or the weight matrices to be used in model predictive control (MPC) such that the MPC has the same performance as a predesigned linear controller in state-feedback form when constraints are not active. This is potentially useful when a successful linear controller already exists and it is necessary to incorporate the constraint-handling capabilities of MPC. This is the case for a wave energy converter (WEC), where the maximum power transfer law is well-understood. In addition to solutions based on numerical optimization, a simple analytical solution is also derived for cases with a short prediction horizon. These methods are applied for the control of an empirically-based WEC model. The results show that the MPC can be successfully tuned to follow an existing linear control law and to comply with both input and state constraints, such as actuator force and actuator stroke.
Highlights
Control design for wave energy converters (WECs) is a critical component in the broaderWEC design problem
Active control strategies are usually developed to achieve the desired goals, but they are significantly related to the WEC design process in that they alter the overall WEC dynamics in terms of system performance and development costs
The model predictive control (MPC) matching problem handled in the previous sections can be applied to a WEC control problem, assuming that a successful feedback controller is already in hand
Summary
Control design for wave energy converters (WECs) is a critical component in the broaderWEC design problem. Control design for wave energy converters (WECs) is a critical component in the broader. A WEC is generally designed to achieve a desired performance goal, such as maximization of electrical power transferred to the grid while minimizing levelized cost of energy and should survive in extreme ocean environments, under various design constraints. This imposes numerous engineering challenges, comprising environmental characterization, modeling, failure detection, and fatigue analysis. Various types of constraints resulting from WEC design or environmental conditions must be considered when developing control systems. A number of control design approaches and frameworks have been applied to WECs in the past
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