Black-box modeling or identification is described, and calculating dynamical time responses of these models is achieved with the aid of simulation toolsThe use of DAEs (differential equations) is elucidated and explained, systems that need another description, namely by using difference equations, state events, or discrete events, are discussed and the use of these for modeling is illustratedParametric models such as FIR, ARX, ARMAX, OE, and BJ models according to Ljung's nomenclature are introducedThe limitations of simulation are emphasized and the numerical integration algorithms are presentedRequires only a prior knowledge of dynamical systems, such as the mathematical models described via differential and difference equations, state models, and frequency responses This book gives an in-depth introduction to the areas of modeling, identification, simulation, and optimization. These scientific topics play an increasingly dominant part in many engineering areas such as electrotechnology, mechanical engineering, aerospace, and physics. This book represents a unique and concise treatment of the mutual interactions among these topics.Techniques for solving general nonlinear optimization problems as they arise in identification and many synthesis and design methods are detailed. The main points in deriving mathematical models via prior knowledge concerning the physics describing a system are emphasized. Several chapters discuss the identification of black-box models. Simulation is introduced as a numerical tool for calculating time responses of almost any mathematical model. The last chapter covers optimization, a generally applicable tool for formulating and solving many engineering problems.