A Novel Closed-Form Expression Obtained by Using Differential Evolution Algorithm to Calculate Pull-In Voltage of MEMS Cantilever

Ak, Cevher; Yıldız, Ali

doi:10.1109/jmems.2018.2812924

Cited by 10 publications

(6 citation statements)

References 41 publications

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“…The DE algorithm, which was developed to optimize a problem by repeatedly trying to make better a potential solution with regard to a required measure of quality, was used as the optimization tool. The DE algorithm has been preferred to have a solution for many numerical problems with a good performance (Ak et al, 2018;Storn et al, 1997). It reaches to correct global minimum point of the cost function very fast when compared to other optimization tools.…”

Section: Problem Formulationmentioning

confidence: 99%

Predicting the Energy Production of a Rooftop Pv Plant by Using Differential Evolution Algorithm

Yıldız

2019

Turkish Journal of Engineering

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In this study, a simple and plain closed-form mathematical expression has been obtained to precisely estimate the monthly production of a rooftop photovoltaic (PV) plant installed in Adana, Turkey. The proposed model is developed by utilizing the Differential Evolution (DE) optimization algorithm based on the PV plant's 5-year (August 2013 -July 2018) real measurement data. The PV plant is a grid-connected rooftop solar PV system located at Kıvanç Textile in Adana, Turkey. The PV system is equipped with an online monitoring system that provides real time data. The study shows the actual energy production is 730 MWh/year on average for 5 years. In order to test the robustness and precision of the present model, it has been compared with the long-term real measurement data of the PV system. The key benefit of the model is giving a convincing prediction of the future production of the PV panel in a simple way. It also does not require any further information other than time. Average percentage error was reached as small as 7.4% for 5-year data.

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Section: Problem Formulationmentioning

confidence: 99%

Predicting the Energy Production of a Rooftop Pv Plant by Using Differential Evolution Algorithm

Yıldız

2019

Turkish Journal of Engineering

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“…Among them, the differential evolution (DE) algorithm and its variants showed excellent performance in competitions held under the IEEE Congress on Evolutionary Computation (CEC) conference series [11,12]. In recent years, DE has been widely applied in diverse fields, such as geography [13], chemistry [14], engineering design [15][16][17][18], image processing [19,20], and software development [21]. Additionally, there are many successful applications of the DE in these fields [22][23][24].…”

Section: Introductionmentioning

confidence: 99%

An Enhancing Differential Evolution Algorithm with a Rank-Up Selection: RUSDE

Zhang

2021

Mathematics

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Recently, the differential evolution (DE) algorithm has been widely used to solve many practical problems. However, DE may suffer from stagnation problems in the iteration process. Thus, we propose an enhancing differential evolution with a rank-up selection, named RUSDE. First, the rank-up individuals in the current population are selected and stored into a new archive; second, a debating mutation strategy is adopted in terms of the updating status of the current population to decide the parent’s selection. Both of the two methods can improve the performance of DE. We conducted numerical experiments based on various functions from CEC 2014, where the results demonstrated excellent performance of this algorithm. Furthermore, this algorithm is applied to the real-world optimization problem of the four-bar linkages, where the results show that the performance of RUSDE is better than other algorithms.

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“…Another recent study proposes a closed-form expression for the pull-in voltage based on the use of the differential evolution optimization algorithm together with the FEM simulation data for hundreds of configurations (Ak and Yildiz, 2018). Other approaches are mathematically rigorous, e.g.…”

Section: Introductionmentioning

confidence: 99%

Simplification by pruning as a model order reduction approach for RF-MEMS switches

Ciuprina

Dumitrache

Lup

et al. 2019

COMPEL

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Purpose This paper proposes an algorithm for the extraction of reduced order models of MEMS switches, based on using a physics aware simplification technique. Design/methodology/approach The reduced model is built progressively by increasing the complexity of the physical model. The approach starts with static analyses and continues with dynamic ones. Physical phenomena are introduced sequentially in the reduced model whose order is increased until accuracy, computed by assessing forces that are kept in the reduced model, is acceptable. Findings The technique is exemplified for RF-MEMS switches, but it can be extended for any device where physical phenomena can be included one by one, in a hierarchy of models. The extraction technique is based on analogies that are carried out for both the multiphysics and the full-wave electromagnetic phenomena and their couplings. In the final model, the multiphysics electromechanical phenomena is reduced to a system with lumped components with nonlinear elastic and damping forces, coupled with a system with distributed and lumped components which represents the reduced model of the RF electromagnetic phenomena. Originality/value Contrary to the order reduction by projection methods, this approach has the advantage that the simplified model can be easily understood, the equations and variables have significance for the user and the algorithm starts with a model of minimal order, which is increased until the approximation error is acceptable. The novelty of the proposed method is that, being tailored to a specific application, it is able to keep physical interpretation inside the reduced model. This is the reason why, the obtained model has an extremely low order, much lower than the one achievable with general state-of-the-art procedures.

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A Novel Closed-Form Expression Obtained by Using Differential Evolution Algorithm to Calculate Pull-In Voltage of MEMS Cantilever

Cited by 10 publications

References 41 publications

Predicting the Energy Production of a Rooftop Pv Plant by Using Differential Evolution Algorithm

Predicting the Energy Production of a Rooftop Pv Plant by Using Differential Evolution Algorithm

An Enhancing Differential Evolution Algorithm with a Rank-Up Selection: RUSDE

Simplification by pruning as a model order reduction approach for RF-MEMS switches

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