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Synthesis of Adequate Mathematical Description as Solution of Special Inverse Problems

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Abstract (2. Language): 
The problem of mathematical simulation of dynamic system characteristics behavior and their adequacy to real experimental data, which correspond to these characteristics, is considered in this paper. The specified problem is still poorly investigated and hardly adapted to formalization. The requirements of related to the adequate mathematical simulation of dynamic system are considered for the case when mathematical description is represented by system of the ordinary differential equations. The conditions are obtained which allow to reduce a problem of the adequate mathematical description to the solution of the several integral equations of the first type. The methods of obtaining of the steady solutions are suggested. The domains of application of the obtained solutions are specified. For a case, when the differential equations of dynamic system are given with errors in coefficients, several variants of synthesis of the adequate mathematical descriptions depending on final goals of this description use are suggested. The examples of the adequate descriptions of concrete dynamic systems are given.
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REFERENCES

References: 

[1] M. Alexik. Modelling and Identification of Eye-Hand Dynamics. Simulation Practice and
Theory, 8, 25-38, 2000.
[2] J. Awrejcewicz and V. Krysko. Introduction to Asymptotic Methods. Taylor and Francis,
2006.
REFERENCES 270
[3] F. Breitenecker, F. Judex, N. Popper, K. Breitenecker, A. Mathe and S. Wassertheurer.
Laura and Petrarca - True Emotions vs. Modelled Emotions. 6-th Vienna Conference on
mathematical Modelling, Vienna, full Papers CD Volume, Vienna Univ. of Technology,
ISBM 978-3-901608-35-3, 46-69, 2009.
[4] Ju. Gelfandbein and L. Kolosov. Retrospective Identification of Perturbations and Interferences.
moscow, Science, 1972.
[5] V. Gubarev. Method of Iterative Identification of Many-Dimensional Systems with Inexact
Data. Part 1. Theoretical basises. Problems of Control and Information, Kiev, Ukraine, 2,
8-26, 2008.
[6] O. Gukov. Algorithms of Iterative Identification of Many-Dimensional Systems. XV International
Conference on Authomatical Control "Authomatics -2008", Odessa: INI,
Ukraine, 774-777, 2008.
[7] H. Hirahara. Engine Modeling and Control System Design Considering Twist of a Crank
Shaft. 6-th Vienna Conference on mathematical Modelling, Vienna - Full Papers CD
Volume, Vienna Univ. of Technology, ISBM 978-3-901608-35-3, 173-179, 2009.
[8] S. Ikeda, S. Migamoto, Y. Sawaragi. Regularization Method for Identification of Distributed
Systems. IY a Symposium IFAC, Identification and Evaluation of Parameters of
Systems, Tbilisi, USSR, Preprint. moscow, 3, 153-162, 1976.
[9] N. Krasovskij. Theory of Motion Control. Science, Moscow, 1968.
[10] V. C. Krass and B. P. Chuprinin. Shape Mathematics in Economics. Mathematical Methods
and Models, Finance and Statistics, Moscow, 2007.
[11] Y. Liu, D. Soffker. Robust Control Approach for Input-Output Linearizable Nonlinear
Systems with Modeling Errors Based on High-Gain PI-Observer. 6-th Vienna Conference
on mathematical Modelling, Vienna, full Papers CD Volume, Vienna Univ. of Technology,
ISBM 978-3-901608-35-3, 193-199, 2009.
[12] Yu. Menshikov. Identification of Moment of Technological Resistance on Rolling Mill.
Journal of Differential Equations and Their Applications in Physics, Dnepropetrovsk University,
Ukraine, 1, 22-28, 1976.
[13] Yu. Menshikov. The Models of External Actions for Mathematical Simulation. System
Analysis and Mathematical Simulation, 14(2), 139-147, 2004.
[14] Yu. Menshikov. About Adequacy of Mathematical Modeling Results. International Conference
"Simulation-2008", Kiev, Ukraine, 119-124, 2008.
[15] Yu. Menshikov. Robotics, Automation and Control. Chapter 7. The Identification of Models
of External Loads, In-Teh is Groatian Branch of I-Tech and Publishing KG, Vienna,
Austria, 2008.
REFERENCES 271
[16] Yu. Menshikov. Algorithms of Construction of Adequate Mathematical Description of
Dynamic System. 6-th Vienna Conference on mathematical Modelling, Vienna - Full
Papers CD Volume, Vienna Univ. of Technology, ISBM 978-3-901608-35-3, 2482-2485,
2009.
[17] Yu. Menshikov. Inverse Problems in Non-classical Statements. International Journal of
Pure and Applied Mathematics, 67(1), 79-96, 2011.
[18] V. Perminov. Mathematical Modeling of Large Forest Fires Initiation. 6-th Vienna Conference
on Mathematical Modelling, Vienna, full Papers CD Volume, Vienna Univ. of
Technology, ISBM 978-3-901608-35-3, 1165-1172, 2009.
[19] W. Porter. Modern Foundations of Systems Engineering. The Macmillan Company, New
York, Collier-Macmillan Limited, London, 1970.
[20] I. Sarmar and A. Malik. Modeling, Analysis and Simulation of a Pan Tilt Platform Based
on Linear and Nonlinear Systems. IEEE/ASME MESA, China, 147-152, 2008.
[21] R. Shannon. Systems Simulation - The Art and Science. Prentice-Hall, Inc., Englewood
Cliffs, New Jersey, 1975.
[22] V. Stepashko. Method of Critical Dispersions as Analytical Apparatus of Theory of Inductive
Modeling. Problems of Control and Information, Kiev, Ukraine, 2, 27-32, 2008.
[23] J. Tillack, S. Noack, K. Noh, A. Elsheikh and W. Wiechert. A Software Framework for
Modeling and Simulation of Dynamic Metabolic and Isotopic Systems. 6-th Vienna Conference
on Mathematical Modelling, Vienna, full Papers CD Volume, Vienna Univ. of
Technology, ISBM 978-3-901608-35-3, 769-778, 2009.
[24] A.Tikhonov and V.Arsenin. Methods of Solution of Incorrectly Problems. Science,
Moscow, 1979.
[25] S. Vilenkin. Application of Regularization for Evaluation of Input Signal under Realization
of Output Signal. Automation and Telemechanics, 21, 52-55, 1968

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