Based on the mechanical model of direct-drive wave energy converters, the relationship among the average output power of a direct-drive wave energy converter, its inherent mechanical impedance, and the equivalent mechanical impedance of the generator is analyzed in the frequency domain to obtain the maximum power extraction condition. In addition, the curves of the average output power of the system under the power control with two degrees of freedom with respect to the control variables are obtained. Based on the characteristics of the curves, a maximum-power-point-tracking (MPPT) strategy is proposed, and the hill-climbing method is used to realize the MPPT. Additionally, the iterative equations and the control flow of the MPPT algorithm are provided. Based on the oscillation phenomenon caused by the measurement error of the average power of actual systems, a window function-based processing method for mean value filtering is proposed, which can further improve the steady-state performance of the hill-climbing-based MPPT strategy. Simulation and experimental results demonstrate that it is an effective and promising power control strategy for direct-drive wave energy converters.

At present, the mainstream solution for the control of wave energy converters (WECs), the model predictive control (MPC)-like method, faces a gap between simulation-based research and practical application. Two of the major difficulties are the online computation burden and the requirement of real-time wave information. In this study, a fast solving strategy is proposed at the level of quadratic programming (QP), where a tailored warm-start algorithm is designed and combined with an early stop technique. Simulations show that only one iteration of interior-point method (IPM) suffices to reach over 95% efficiency of the exact MPC, which significantly speeds up the computation. The fast strategy is then deployed on the real-time controller of a prototype WEC platform. During this implementation, the instantaneous wave force is estimated by a Kalman filter entirely based on the basic feedback signals: position, velocity, and the generator current, while future wave forces are predicted by an autoregressive model. The wave tank test confirms that the proposed fast MPC is capable of being executed at a high frequency, achieving stable operations within constraints, and reaching satisfactory energy efficiency under real wave-body interactions.

In order to get good control performance in permanent magnet synchronous motor (PMSM) control fields, the accurate permanent magnet flux linkage (rotor flux linkage) value is needed. For stator flux estimation and full order or reduced order observer, the rotor flux linkage is treated as a known and constant parameter. But in applications, the rotor flux linkage can vary in a wide range. In this paper, a rotor flux linkage observer based on Kalman filter is presented. After rearranging the equation of interior permanent magnet synchronous motor (IPMSM), a new set of variables is defined. By choosing the new set of variables and the rotor flux linkage as state variables, a three-order Kalman filter is constructed. For surface mounted PMSM (SPMSM), by substituting L_d = L_q to the proposed Kalman filter, the rotor flux linkage of SPMSM can be observed, too. The performance of the proposed observer is verified by simulation and experiments. Both the simulation results and experimental results show that the Kalman filter estimates the rotor flux linkage accurately

In this study, the maximum power extraction condition for a direct-drive wave energy converter in irregular waves in the time domain was proven and described using the variational method. Thus, a real-time optimal power control law was proposed, which contained a noncausal part. To determine this law, a classical controller requires information about the future wave excitation force. The prediction of a wave excitation force is either too costly or less accurate. This study presents a novel optimal power control method based on a back propagation (BP) neural network without wave prediction. The network was used to learn the input–output mapping relationships of the noncausal part, and it used the history data of the wave excitation force as the input. The setting and training of the network models are discussed in detail. The history data of the wave excitation force were identified using a Kalman filter. The simulation and experiment demonstrated that the proposed method was valid, effective, and superior to some existing methods.

In the wave energy converter (WEC) optimal control problem, the well-developed model predictive control (MPC) faces the trade-off between energy extraction performance and online computation burden when choosing the length of optimization horizon. In this work, a novel MPC problem formulation is proposed, which includes a terminal value function and a terminal constraint set. The terminal value function is derived by further calculating the system trajectory beyond the optimization horizon based on a pre-chosen “rollout” policy, which incorporates more future information and improves energy extraction. The linear reactive control is chosen as the rollout policy, under which a policy improvement theorem of the WEC system is derived. The terminal constraint set is a simple control invariant set that ensures the recursive feasibility of MPC. Extensive simulations show that the proposed reactive rollout MPC can achieve close-to-optimal performance with a very short optimization horizon, reducing the online computation burden significantly.

Interior permanent magnet synchronous motor (IPMSM) which has magnets buried in the rotor core possesses mechanically robust construction, can be used in high-speed application by incorporating the field-weakening technique. Performance control of IPMSM needs accurate information of rotor angle and angular speed. During recent years, sensorless drives of permanent-magnet synchronous motors have attracted much attention. Traditional back EMF-based methods are not suitable for IPMSM because their salient pole. In this paper, a scheme of MRAS method for IPMSM is described, which is very simple to be implemented. In this scheme, only the stator currents and the DC bus voltage are needed and satisfactory performance can be achieved. The simulation and experimental results confirm the validity of proposed method