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Suitable for courses in System Identification, this book provides a description of the theory, methodology and practice of System Identification - the science of building mathematical models of dynamic systems by observing input/output data. It includes material on subspace methods, non-linear black box models - such as neural networks.

This textbook is designed for an advanced course in control theory. Basic courses in control typically cover linear time invariant systems with one input and one output. Since industrial processes often have several inputs and outputs and contain nonlinearities, these topics need to be covered in a second course. The book explains developments in multivariable and nonlinear control techniques, and looks at tools for computer aided design, for example Matlab and its toolboxes.

The DMV seminar "Stochastische Approximation und Optimierung zufalliger Systeme" was held at Blaubeuren, 28. 5. -4. 6. 1989. The goal was to give an approach to theory and application of stochas tic approximation in view of optimization problems, especially in engineering systems. These notes are based on the seminar lectures. They consist of three parts: I. Foundations of stochastic approximation (H. Walk); n. Applicational aspects of stochastic approximation (G. PHug); In. Applications to adaptation: ugorithms (L. Ljung). The prerequisites for reading this book are basic knowledge in...