scholarly journals Identificación del modelo de un motor de DC mediante métodos gráficos y métodos paramétricos

2017 ◽  
Vol 4 (2) ◽  
Author(s):  
DIEGO VERDUGO ORMAZA ◽  
JEAN MATA QUEVEDO ◽  
CESAR CORONEL GONZALEZ ◽  
TRAJANO GONZALEZ REDROVAN
Keyword(s):  
Mathematical Models ◽  
Dynamic Systems ◽  
Selection Criteria ◽  
Parametric Identification ◽  
Model Structure ◽  
Parametric Methods ◽  
System Behavior ◽  
Generator System ◽  
Arx Model ◽  
Graphic Methods

Este artículo presenta el estudio para conseguir el modelo de un motor-generador (planta), se emplean métodos gráficos o paramétricos que nos servirán como herramientas para representar dicho sistema de forma matemática. Se han adquirido muestras a través de una DAQ del comportamiento del sistema ante un escalón y una señal PRBS, los datos obtenidos se procesaron a través del software MATLAB y el toolbox IDENT, donde por medio de  criterios de selección se obtiene un modelo ARX. Las técnicas estudiadas fueron: identificación paramétrica con la aplicación de una señal PRBS y estructura de modelo ARX e identificación no paramétrica con la aplicación de métodos gráficos. Luego se realiza una comparación entre los datos reales con los diferentes métodos aplicados y se obtiene que las respuestas son muy similares. La identificación de sistemas nos sirve para construir modelos matemáticos de sistemas dinámicos basándonos en los datos observados, con lo cual se tiene un conjunto de técnicas para levantar un proceso. Abstract This article presents the study to obtain the model of an engine-generator system (plant), we use graphical or parametric methods that will serve as tools to represent said system in a mathematical way. The signs were acquired through a DAQ system behavior before a step and PRBS signal, the data was processed through MATLAB software and IDENT toolbox, where through selection criteria described subsequently obtained an ARX model. The techniques studied were: parametric identification with the application of a PRBS signal and ARX model structure and non-parametric identification with the application of graphic methods. Then a comparison is made between the actual data with the different methods applied and it is obtained that the answers are very similar. The identification of systems serves to construct mathematical models of dynamic systems based on observed data, which has a set of techniques to build a process.    

scholarly journals Towards Generative Design of Computationally Efficient Mathematical Models with Evolutionary Learning

Entropy ◽  
2020 ◽  
Vol 23 (1) ◽  
pp. 28
Author(s):  
Anna V. Kalyuzhnaya ◽  
Nikolay O. Nikitin ◽  
Alexander Hvatov ◽  
Mikhail Maslyaev ◽  
Mikhail Yachmenkov ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Learning Approach ◽  
Model Structure ◽  
Evolutionary Learning ◽  
Learning Models ◽  
Computationally Efficient ◽  
Performance Models ◽  
Generative Design ◽  
Computational Resources ◽  
Machine Learning Models

In this paper, we describe the concept of generative design approach applied to the automated evolutionary learning of mathematical models in a computationally efficient way. To formalize the problems of models’ design and co-design, the generalized formulation of the modeling workflow is proposed. A parallelized evolutionary learning approach for the identification of model structure is described for the equation-based model and composite machine learning models. Moreover, the involvement of the performance models in the design process is analyzed. A set of experiments with various models and computational resources is conducted to verify different aspects of the proposed approach.

scholarly journals ANALISIS RULE INFERENSI FUZZY MAMDANI DALAM MENENTUKAN IPK AKHIR

2017 ◽  
Vol 1 (1) ◽  
pp. 22
Author(s):  
Khairul Saleh
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Mathematical Models ◽  
Dynamic Systems ◽  
Fuzzy Systems ◽  
Chaotic Dynamics ◽  
Complex Dynamic ◽  
Grade Point ◽  
Complex Dynamic Systems ◽  
Decision Making System

Abstract - In the world of education to achieve the level of success, of course, they have a benchmark for the success of students, one of them is the Grade Point Average (GPA). The purpose of this study is to determine the final GPA so that later it can be used as a reference to predict the success rate of students. The issue of decision-making systems using Fuzzy systems is very suitable for definite reasoning or estimation, especially for systems with strict mathematical models that are difficult to get a definite decision. Fuzzy logic can be used to describe a system of chaotic dynamics, and fuzzy logic can be useful for complex dynamic systems where solutions to common mathematical models cannot work well. The Mamdani method computes efficiently and works well with optimization and adaptive techniques, which makes it very good in control problems, especially for dynamic non-linear systems. Keywords - Cumulative Achievement Index (GPA), fuzzy system, decision making system, mamdani information

scholarly journals Parametric Reduction of Mathematical Models of Dynamic Systems

2018 ◽  
pp. 39-55
Author(s):  
A. A. Verlan ◽  
◽  
O. A. Diachuk ◽  
E. A. Palahina ◽  
V. V. Palahin ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Dynamic Systems

scholarly journals Risks associated with the transportation of hazardous materials on public roads

2018 ◽  
Vol 231 ◽  
pp. 05004
Author(s):  
Eligiusz Mieloszyk ◽  
Anita Milewska
Keyword(s):  
Mathematical Models ◽  
Dynamic Systems ◽  
Negative Impact ◽  
Significant Proportion ◽  
Water Reservoir ◽  
Hazardous Materials ◽  
Road Users ◽  
Distributed Parameters ◽  
Surrounding Environment ◽  
Flow Surface

A significant proportion of the transport of hazardous materials is carried out on public roads. Therefore, the safety of such transport is becoming increasingly important. Every catastrophe involving hazardous materials has a negative impact on direct road users and the surrounding environment, becauses its range is mostly not local. It follows that in the event of such catastrophe, its effects should be minimized. This is possible only when we know the mechanism of spreading effects of a catastrophe involving hazardous materials. Those effects are spread by two basic media: ground (in particular water in the ground) and air. Sometimes those effects are spread by water, while the catastrophe has occurred near a water reservoir or watercourse with a free flow surface. In extreme cases, this can even lead to an ecological disaster. Dynamic systems, especially those with distributed parameters, can be used to describe the mechanism of the disaster's spread. Properties of phenomena accompanying analyzed catastrophes are well reflected in their linear or non-linear mathematical models [1,2], which are analyzed by various operator methods [3].

Detection of Model Parameter Mismatch Using Simplified Partial Correlation Analysis for Closed-Loop System

2014 ◽  
Vol 625 ◽  
pp. 398-401
Author(s):  
Nur Hidayah Kamal Iqbal ◽  
Nooryusmiza Yusoff ◽  
Lemma Dendena Tufa
Keyword(s):  
Correlation Analysis ◽  
Partial Correlation ◽  
Closed Loop ◽  
Loop System ◽  
Model Structure ◽  
Closed Loop System ◽  
Partial Correlation Analysis ◽  
Parameter Mismatch ◽  
Arx Model ◽  
Model Parameter

Partial correlation analysis is used in detecting the model-plant mismatch as it will give accurate location of mismatched submodel. In this work of model parameter mismatch detection in closed-loop system, a simplified method of partial correlation analysis is proposed. In this method, the identification step for input sensitivities relating setpoints and manipulated variables,Sru, is omitted due the ability of ARX model structure to capture the dynamic of the input-output data even though in the presence of unmeasured disturbance in closed-loop system. The ARX model structure is implemented in decorrelating the observed data from the correlated inputs. By using the ARX model, the mismatch is detected at the precise location compared to the detection using FIR decorrelation model.

Based on Walsh packet parametric identification technique for dynamic systems

PAMM ◽  
2005 ◽  
Vol 5 (1) ◽  
pp. 777-778
Author(s):  
Magdalena Napiorkowska-Alykow ◽  
Wojciech Glabisz
Keyword(s):  
Dynamic Systems ◽  
Parametric Identification ◽  
Identification Technique
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