Power Maximization in Wave-Energy Converters Using Sampled -Data Extremum Seeking /

Ocean waves bear huge, largely untapped energy which has drawn people's attention in recent decades. With the technology of wave-energy converters(WECs), the extraction of wave energy involves the process of energy conversion, which relates to the concern of efficiency as well as the constraints it introduces. In this work, we consider the problem of power maximization in wave-energy converters modeled as point-absorbers. We focus on the method of sampled-data extremum-seeking, where we give assumptions based on which the semiglobal practical asymptotic stability of the interconnected system is characterized. It is worth noting that the novelty lies in our assumptions on the discrete-time class of systems and constrained control inputs. Besides the exploration in the theoretical aspect, we also propose the Numerical Extremum -Seeking (NES) algorithm for the plant of WEC. We prove that it is capable of solving the power maximization problem while ensuring the stability of the system. The analysis of NES algorithm is based on the aforementioned theory along with a Poincare map technique and a gradient- projection method. Finally, we show the functionality of the proposed algorithm in simulation results. In addition to the regular-wave condition, we present the simulation for a more practical scenario, i.e., the irregular-wave cas