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Modelling of Simplified Dynamical Systems 2002 ed. [Kõva köide]

  • Formaat: Hardback, 171 pages, kõrgus x laius: 235x155 mm, kaal: 950 g, VI, 171 p., 1 Hardback
  • Ilmumisaeg: 12-Sep-2002
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3540437622
  • ISBN-13: 9783540437628
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  • Formaat: Hardback, 171 pages, kõrgus x laius: 235x155 mm, kaal: 950 g, VI, 171 p., 1 Hardback
  • Ilmumisaeg: 12-Sep-2002
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3540437622
  • ISBN-13: 9783540437628
Problems involving synthesis of mathematical models of various physical systems, making use of these models in practice and verifying them qualitatively has - come an especially important area of research since more and more physical - periments are being replaced by computer simulations. Such simulations should make it possible to carry out a comprehensive analysis of the various properties of the system being modelled. Most importantly its dynamic properties can be - dressed in a situation where this would be difficult or even impossible to achieve through a direct physical experiment. To carry out a simulation of a real, phy- cally existing system it is necessary to have its mathematical description; the s- tem being described mathematically by equations, which include certain variables, their derivatives and integrals. If a single independent variable is sufficient in - der to describe the system, then derivatives and integrals with respect to only that variable will appear in the equations. Differentiation of the equation allows the integrals to be eliminated and produces an equation which includes derivatives with respect to only one independent variable i. e. an ordinary differential equation. In practice, most physical systems can be described with sufficient accuracy by linear differential equations with time invariant coefficients. Chapter 2 is devoted to the description of models by such equations, with time as the independent va- able.

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Springer Book Archives
Introduction
1(2)
Mathematical Models
3(34)
Differential equations
3(4)
Transfer function
7(1)
State equations
8(8)
Models of standards
16(6)
Examples
22(15)
System Parameters
37(6)
Overshoot
37(1)
Damping factor
38(1)
Half-time
39(1)
Equivalent time delay
39(1)
Time constants
40(1)
Resonance angular frequency
41(2)
Model Synthesis
43(41)
Algebraic polynomials
43(2)
The least squares method
45(2)
Cubic splines
47(4)
Square of frequency response method
51(2)
The Maclaurin series method
53(3)
Multi-inertial models
56(5)
Weighted means method
61(5)
Smoothing functions
66(2)
Kalman filter
68(2)
Examples
70(14)
Simplification of Models
84(40)
The least-squares approximation
85(7)
The Rao-Lamba method
92(1)
Criterion of consistency of model response derivatives at the origin
93(1)
Reduction of state matrix order with selected eigenvalues retained
94(5)
Simplification of models using the Routh table coefficients
99(1)
Simplification of models by means of Routh table and Schwarz matrix
100(6)
Simplification of models by comparison of characteristic equation coefficients
106(1)
Examples
107(17)
Maximum Mapping Errors
124(19)
Input signals with one constraint
125(9)
Input signals with two constraints
134(4)
Examples
138(5)
Signals Maximising the Integral-Square-Error in the Process of Models Optimisation
143(22)
Optimisation of models in the case of the high value of primary mapping error. Optimisation of Butterworth filters
144(1)
Examples
145(14)
Optimisation of models in the case of the small value of primary mapping error
159(1)
Examples
159(6)
References 165(4)
Index 169