This paper proposes a full order nonlinear dynamic model for a DC-DC Multilevel Boost Converter (MBC). This model is based on the equivalent circuits that depend on the commutation states of the converter. A reduced order nonlinear model to approximate the dynamics of the MBC containing any number of levels is also obtained. In addition, an input-output feedback linearization controller is derived and implemented. The stability of the closed loop system is analyzed. A Linux-based real-time software is employed for obtaining the experimental results of the closed loop system.
This paper aims at summarizing various methods used for representing and estimating the power coefficient in wind turbines, such as exponential, sinusoidal and polynomial models, as well as mathematical tools known as state observers. We present an exhaustive bibliographic review of the models used to calculate the power coefficient, given that this type of studies are scarce nowadays. In addition, we propose models that can be satisfactorily used for various analyzes of wind energy conversion systems, such as the representation by a polynomial function of fourth degree and the models based on the stochastic probability function. The relevance of this work is supported by the advantages and disadvantages of the various models and estimators of the power coefficient, which are presented at the end of the article in a comparative table with the purpose of offering to the reader a general summary. Ultimately, this review aims at helping researchers, students, university professors and those who wish to venture into this field, even though they do not have much experience, to establish a quick synthesized understanding of the different models and representations of the power coefficient.
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