Articolele autorului Marius Giuclea
Link la profilul stiintific al lui Marius Giuclea

Analytical methods to assess linear models for experimental hysteretic loops
Semi-active Suspension Control

Describes the control of semi-active suspension which is more effective than traditional and widely-covered passive suspension and much cheaper than very specialised active suspension Compares the behaviour of magnetorheological dampers, already on the market, with that of friction dampers still under development Shows the reader how the human body reacts to vibration and the benefits of different damping regimes

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An analytical approach for approximation of experimental hysteretic loops by Bouc-Wen model

In this paper an analytical method is developed to identify the Bouc-Wen model parameters from the experimental data of periodic loading tests. The model parameters are determined by closed analytical relationships such as the predicted and experimental hysteresis loops to have exactly the same maximum force values and coordinates of loop- axes crossing points. Asymmetric hysteretic characteristics are modeled by sewing the solutions of two different

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On statistical pattern with fuzzy data

In this paper, a general regression model with input-output trapezoidal fuzzy data, derived from a previous algorithm for triangular data, is discussed. Finally, an implementation of these results with application in estimating the efficiency of a decision making units model is presented.

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Identification of an extended Bouc-Wen model with application to seismic protection through hysteretic devices

In this paper is proposed an extended Bouc–Wen model for improving its capability to approximate experimental symmetric hysteretic loops. On the basis of the generalized equation there are defined integral and differential conditions that describe the essential geometric properties of a hysteretic curve. Next, a new method based on Genetic Algorithms is developed to identify the Bouc–Wen model parameters from experimental hysteretic loops obtained

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Model parameter identification for vehicle vibration control with magnetorheological dampers using computational intelligence method