This paper presents the application of nonlinear model predictive control (NMPC) to a point absorber wave energy converter (WEC). Model predictive control (MPC) is generally a promising approach for WECs, since system constraints and actuator limits can be taken into account. Moreover, it provides a framework for defining optimal energy capture and it can benefit from predictions. Due to possible nonlinear effects, such as the mooring forces, an NMPC is proposed in this paper, whose performance is compared to that of a linear MPC. Both controllers are supposed to control a nonlinear point absorber model. Computer simulations show that the proposed NMPC is able to optimize the energy capture while satisfying system limits.Index Terms-Nonlinear model predictive control, point absorber, wave energy converter.

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Most of the research on wave energy conversion has been focused on the characterization of the dynamic behavior of arrays of uncontrolled wave energy converters (WECs) in specific configurations, in order to quantify changes in the wave fields and absorbed power without active control. To maximize wave energy conversion, however, it is necessary to apply active control techniques to the WECs that conform the array. In this paper, we propose the application of decentralized model predictive control (MPC) to the elements of an array by considering each individual WEC as a subsystem. Each decentralized MPC optimizes the absorbed power of its own WEC under the same input and state constraints that a centralized MPC otherwise would.Index Terms-Model predictive control (MPC), point absorber, wave energy converter (WEC) arrays.

This study presents a model predictive control (MPC) scheme for a wave energy converter (WEC); in particular, for a buoy-type point absorber. The WEC is a two-body system which is taut-moored to the sea floor with three cables. Much research has been done recently to achieve optimal operation of WECs. The goal is to maximise the power conversion without violating system limits. In practice, there are physical constraints on position, velocity and the power takeoff (PTO) force. MPC is a promising and beneficial approach to achieve this goal. It poses a control formulation including constraints in a natural way. Furthermore, MPC can exploit predictions for the sea motion a standard MPC approach always needs a reference trajectory. For one-body point absorber, an optimal velocity trajectory can be calculated. However, an optimal trajectory is not easily available for the two-body case. The proposed formulation in the presented work does not require an optimal trajectory. For this reason it is possible to apply this MPC scheme to a two-body model as well. This work demonstrates that the proposed control algorithm optimises the power extraction without violating the system constraints. Finally, the performance of MPC is compared to linear passive load control through simulation.

Several approaches for travel time data collection based on the reading of time-stamped media access control addresses fromBluetooth-enabled devices have been reported in the literature recently. This new approach offers a number of advantages over more conventional methods, including lower costs of hardware and software, the volume of data that can be collected over time, and ease of implementation. A fundamental component that may affect the quantity and the quality of the travel time samples collected with a Bluetooth-based system is the antenna type utilized. Antenna characteristics such as polarization and gain must be matched to specific application environments to optimize the performance of a Bluetooth reader unit. However, experimental data that focuses on antenna characterization as it relates to the use of Bluetooth technology to assess the performance of transportation facilities is lacking. In this study, five different types of antennas were characterized to assess their suitability to support a Bluetooth-based travel time data collection system. The results indicate that vertically polarized antennas with gains between 9dBi and 12dBi are good candidates for travel time data collection. Also, different antenna types are better suited to different uses of the Bluetooth-based system. If the main focus is the collection of travel time data, then an antenna with a lower sampling rate may provide more accurate travel time samples.

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Ocean wave energy has the potential to significantly contribute to sustainable power generation in coastal regions. Much of the research effort has gone into developing time domain state space models of point absorber wave energy converters (WECs) and subsequently into model-based optimal control to efficiently harvest the maximum possible amount of energy. The resulting controllers require knowledge of the states of the WEC in order to achieve the design goals. The purpose of this paper is to design and apply an extended Kalman filter-based estimation algorithm to a nonlinear two-body WEC model and to evaluate its performance in conjunction with a model predictive controller (MPC), which maximizes energy yield while satisfying operational constraints.Index Terms-Kalman filter, model predictive control (MPC), nonlinear point absorber, wave energy converters (WECs).

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