scholarly journals In Dynamic Systems with Fuzzy A - Cutting Determination of Membership Function Ranges

2020 ◽  
Vol 1 (1) ◽  
pp. 19-29
Author(s):  
Fatih Topaloğlu ◽  
Hüseyin Pehlivan
Keyword(s):  
Membership Function ◽  
Dynamic Systems

Model Verification of Mixed Dynamic Systems

1978 ◽  
Vol 100 (2) ◽  
pp. 266-273 ◽  
Author(s):  
J. D. Chrostowski ◽  
D. A. Evensen ◽  
T. K. Hasselman
Keyword(s):  
Experimental Data ◽  
Parameter Estimation ◽  
Dynamic Systems ◽  
Statistical Parameter ◽  
Model Verification ◽  
Passive Networks ◽  
Parameter Values ◽  
Basic Configuration ◽  
General Method

A general method is presented for using experimental data to verify math models of “mixed” dynamic systems. The term “mixed” is used to suggest applicability to combined systems which may include interactive mechanical, hydraulic, electrical, and conceivably other types of components. Automatic matrix generating procedures are employed to facilitate the modeling of passive networks (e.g., hydraulic, electrical). These procedures are augmented by direct matrix input which can be used to complement the network model. The problem of model verification is treated in two parts; verification of the basic configuration of the model and determination of the parameter values associated with that configuration are addressed sequentially. Statistical parameter estimation is employed to identify selected parameter values, recognizing varying degrees of uncertainty with regard to both experimental data and analytical results. An example problem, involving a coupled hydraulic-mechanical system, is included to demonstrate application of the method.

scholarly journals Formulation of the membership function and determination of the input of fuzzy loads in the structural fuzzy analyzing problem

2007 ◽  
Vol 29 (2) ◽  
pp. 117-126
Author(s):  
Nguyen Van Pho
Keyword(s):  
Membership Function ◽  
Input Parameter ◽  
Design Standards ◽  
Input Parameters ◽  
Triangular Membership Function ◽  
Probabilistic Density Function ◽  
Fuzzy Parameters ◽  
Selection Of ◽  
The Membership Function

The fuzzy analyzing process consists of different steps. In this paper, the author considers only the method for formulation of the membership function of fuzzy loads acting on the structure. Based on the membership function of fuzzy loads, the combinations of deterministic of the regression analyzing process will be determined. The membership function of fuzzy loads is selected by the triangular membership function. It is in conformity with the concept on selection of loads in the design standards. The combination of inputs for the analyzing process will be determined, based on the number of present times of the value of input parameters (including the deterministic parameters, fuzzy parameters and the random ones) in the schema of analysis. The number of present times of input parameters is either proportional to value of the corresponding membership function or to the value of the probabilistic density function. A method for determining the appropriate combination of deterministic inputs so that each input parameter will present only one time in each combination is proposed. To illustrate the proposed method, an example on the determination of input combinations of tornado's velocity in Vietnam is presented.

scholarly journals PENENTUAN JURUSAN PADA PROSES PENERIMAAN MAHASISWA DENGAN PENDEKATAN LOGIKA FUZZY

2021 ◽  
Vol 8 (1) ◽  
pp. 193-200
Author(s):  
Ari Purno Wahyu ◽  
Umi Hayati
Keyword(s):  
Membership Function ◽  
Fuzzy Inference ◽  
Function Type ◽  
Academic Field ◽  
Computer Knowledge ◽  
Selection Test ◽  
The Right ◽  
High Level ◽  
Selection Of

Choosing a major is not an easy matter. There are many factors that must be taken into account and carefully thought out so that in choosing a major, it will cause big losses. There are many ways to determine the selection of majors, one of which is by using fuzzy logic. Determination of majors is determined from the results of the selection test in the academic field with the subjects of Mathematics, English and Computer Knowledge. With the aim of recommending the selection of the right major according to academic abilities and improving quality. By using the fuzzy inference model Mamdani max-min method. The system simulation was tried using the MATLAB Fuzzy Toolbox software. The system design is carried out in several stages, namely: (1) formation of fuzzy sets, (2) formation of rules, (3) determination of the composition of rules, and (4) confirmation (defuzzification). Defuzzification is carried out using the Composite Moment method, with the types of membership functions used are mf-triangular, mf-trapezoid and mf-gaussian. From the results of the tests carried out, it shows that the mf-triangular and mf-trapezoid membership function types produce almost the same level of accuracy. While the membership function type mf-gaussian produces a high level of accuracy for mathematics by 87.50%, English 100% and computer knowledge 81.58%.  

scholarly journals The Invariance Determination of the Complex Electrical System Output of

2021 ◽  
Vol 264 ◽  
pp. 01024
Author(s):  
Tokhir Makhmudov
Keyword(s):  
Dynamic Systems ◽  
Matrix Theory ◽  
Controller Synthesis ◽  
Electrical System ◽  
Electrical Systems ◽  
System Output ◽  
System Mode ◽  
Small Disturbances

This article discusses the issues of applying the technology of embedding systems to study the invariance of the output of complex controlled electrical systems under small disturbances as stationary deterministic multidimensional dynamic systems. The technique of controller synthesis based on the modern matrix theory is presented. The synthesis of the regulator of the model of a multi-machine electrical system is obtained, which makes it possible to analyze the influence of the parameters of the electrical system mode.

Determination of Significance of Stress Stiffening Effects in Flexible Multibody Dynamic Systems

1992 ◽  
Author(s):  
Jeha Ryu ◽  
Sang Sup Kim ◽  
Sung-Soo Kim
Keyword(s):  
Dynamic Simulation ◽  
Dynamic Systems ◽  
Stiffness Matrix ◽  
Multibody Systems ◽  
Flexible Body ◽  
Multibody Dynamic ◽  
Flexible Multibody ◽  
Multibody Dynamic System ◽  
Modal Stress

Abstract This paper presents a criterion for determining whether or not a flexible multibody dynamic system reveals stress stiffening effects. In the proposed criterion, the eigenvalue variation that results from adding the modal stress stiffness matrix to the conventional linear modal stiffness matrix is examined numerically before actual dynamic simulation. If the variation is sufficiently large for any flexible body, then stress stiffening effects are said to be significant and must be included in dynamic simulation of flexible multibody systems. Since the criterion uses the most general stress stiffness matrix, which can be represented as a function of applied and constraint reaction loads as well as of a system of 12 inertial loads, this criterion is applicable to any general flexible multibody dynamic systems. Several numerical results are presented to show the effectiveness of the proposed criterion.

scholarly journals Physiologically Based Structure of Mean Residence Time

2012 ◽  
Vol 2012 ◽  
pp. 1-4
Author(s):  
Mária Ďurišová
Keyword(s):  
Pharmacokinetic Parameter ◽  
Residence Time ◽  
Dynamic Systems ◽  
Mean Residence Time ◽  
Structural Identification ◽  
Linear Dynamic Systems ◽  
Linear Dynamic ◽  
Physiologically Based

A mean residence time (MRT) is an important pharmacokinetic parameter. To the author's knowledge, however, a physiologically based structure of MRT (thereafter MRT structure) has not been published so far. Primarily this is because MRT structures cannot be identified by traditional pharmacokinetic methods used for the determination of MRT. Therefore, tools from the theory of linear dynamic systems were used for the structural identification of MRT in this study. The MRT structure identified is physiologically meaningful. Accordingly, it seems that the MRT structure identified may contribute to already established knowledge about MRT.

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