Continuous System Modeling

ISBN-13: 9780387975023 / Angielski / Twarda / 1991 / 756 str.

Francois E. Cellier; Jurgen Greifeneder; Fran??ois E. Cellier

Opis

Modeling and Simulation have become endeavors central to all disciplines of science and engineering. They are used in the analysis of physical systems where they help us gain a better understanding of the functioning of our physical world. They are also important to the design of new engineering systems where they enable us to predict the behavior of a system before it is ever actually built. Modeling and simulation are the only techniques available that allow us to analyze arbitrarily non-linear systems accurately and under varying experimental conditions. Continuous System Modeling introduces the student to an important subclass of these techniques. They deal with the analysis of systems described through a set of ordinary or partial differential equations or through a set of difference equations. This volume introduces concepts of modeling physical systems through a set of differential and/or difference equations. The purpose is twofold: it enhances the scientific understanding of our physical world by codifying (organizing) knowledge about this world, and it supports engineering design by allowing us to assess the consequences of a particular design alternative before it is actually built. This text has a flavor of the mathematical discipline of dynamical systems, and is strongly oriented towards Newtonian physical science.

Spis treści

1 Introduction, Scope, and Definitions.- 2 Basic Principles of Continuous System Modeling.- 3 Principles of Passive Electrical Circuit Modeling.- 4 Principles of Planar Mechanical System Modeling.- 5 Hierarchical Modular Modeling of Continuous Systems.- 6 Principles of Active Electrical Circuit Modeling.- 7 Bond Graph Modeling.- 8 Modeling in Nonequilibrium Thermodynamics.- 9 Modeling Chemical Reaction Kinetics.- 10 Population Dynamics Modeling.- 11 System Dynamics.- 12 Naïve Physics.- 13 Inductive Reasoning.- 14 Artificial Neural Networks and Genetic Algorithms.- 15 Automated Model Synthesis.