The frequency domain evaluation of mathematical models for dynamic systems

AIChE Journal ◽  
1967 ◽  
Vol 13 (2) ◽  
pp. 374-378 ◽  
Author(s):  
James R. Hays ◽  
William C. Clements ◽  
Thomas R. Harris
Keyword(s):  
Mathematical Models ◽  
Frequency Domain ◽  
Dynamic Systems

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].

Treating Uncertainties in Multibody Dynamic Systems Using a Polynomial Chaos Spectral Decomposition

2004 ◽  
Author(s):  
Corina Sandu ◽  
Adrian Sandu ◽  
Brendan J. Chan ◽  
Mehdi Ahmadian
Keyword(s):  
Frequency Domain ◽  
Dynamic Systems ◽  
Time Domain ◽  
Spectral Decomposition ◽  
Polynomial Chaos ◽  
Model Uncertainties ◽  
Dynamic Simulations ◽  
Computational Tools ◽  
Model Complex ◽  
Multibody Dynamic

This study addresses the critical need for computational tools to model complex nonlinear multibody dynamic systems in the presence of parametric and external uncertainty. Polynomial chaos has been used extensively to model uncertainties in structural mechanics and in fluids, but to our knowledge they have yet to be applied to multibody dynamic simulations. We show that the method can be applied to quantify uncertainties in time domain and frequency domain.

Optimization of Complex Dynamic Systems With Respect to Their Behavior in Time and Frequency Domain

2011 ◽  
Author(s):  
Matthias Marx ◽  
Chunsheng Wei ◽  
Dirk So¨ffker
Keyword(s):  
Frequency Domain ◽  
Dynamic Systems ◽  
Power Flow ◽  
Dynamical Behavior ◽  
Magnetic Bearing ◽  
Rotor System ◽  
Active Magnetic Bearing ◽  
Design Parameters ◽  
Powertrain System ◽  
Aging Mechanisms

This paper describes an integrated optimization process of dynamic systems including design parameters and control algorithms. In contrast to known approaches the developed approach is based on an optimization loop including the evaluation of the dynamical behavior of technical systems with respect to the behavior and related properties in time and frequency domain. This includes as well the behavior of the system, the objective function as the formulation of the restrictions to be considered for the dynamical behavior (stationary and instationary). The proposed approach is declared in detail and will be illustrated using two typical technical applications as examples. The first application example is the optimization of the control system of an active magnetic bearing (AMB) rotor system. Hereby the modeling of the AMB rotor system is briefly introduced. An H∞ controller is designed for the control of the system. The performance both in time and frequency domain is optimized in parallel. The algorithm will be explained by simulation examples. The second example is the optimization of the pow-ermanagement system of a fuel cell/supercap-based hybrid electric powertrain. Hereby the modeling of the electric power flow within the powertrain system is demonstrated and its influence on certain system properties like availability, efficiency, and typical aging mechanisms is discussed. The proposed method leads to near-optimal results in a few steps for both of the systems introduced.

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