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Sinopsis
Mathematical models of real life systems and processes are essential in today s industrial work. To be able to construct such models is therefore a fundamental skill in modern engineering. This is a book about how to build models both from first principles in physics and from information in collected input and output measurements from the system. Physical modelling is nowadays typically done by object oriented software, such as Modelica and Matlab s Simscape. These techniques are described in the book, together with their theoretical and mathematical underlying principles. Domain-independent methods, such as following energy flows in bond graphs gives a useful background for understanding object oriented modelling. Both classical state-space models and general differential algebraic equations (DAE) are treated. The book also gives a comprehensive treatment of system identification, that is, techniques to estimate mathematical models from measured system inputs and outputs. Both linear and non-linear models are treated, including artificial neural networks. The text is related to the Swedish text Modellbygge och Simulering, Studentlitteratur, 2003.
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Reseña del editor
Mathematical models of real life systems and processes are essential in today’s industrial work. To be able to construct such models is therefore a fundamental skill in modern engineering. This is a book about how to build models both from first principles in physics and from information in collected input and output measurements from the system. Physical modelling is nowadays typically done by object oriented software, such as Modelica and Matlab’s Simscape. These techniques are described in the book, together with their theoretical and mathematical underlying principles. Domain-independent methods, such as following energy flows in bond graphs gives a useful background for understanding object oriented modelling. Both classical state-space models and general differential algebraic equations (DAE) are treated. The book also gives a comprehensive treatment of system identification, that is, techniques to estimate mathematical models from measured system inputs and outputs. Both linear and non-linear models are treated, including artificial neural networks. The text is related to the Swedish text Modellbygge och Simulering, Studentlitteratur, 2003.
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