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System Identification
The field's leading text, now completely updated. Modeling dynamical systems — theory, methodology, and applications. Lennart Ljung's System Identification: Theory for the User is a complete, coherent description of the theory, methodology, and practice of System Identification. This completely revised Second Edition introduces subspace methods, methods that utilize frequency domain data, and general non-linear black box methods, including neural networks and neuro-fuzzy modeling. The book contains many new computer-based examples designed for Ljung's market-leading software, System Identification Toolbox for MATLAB. Ljung combines careful mathematics, a practical understanding of real-wor...
Control Theory
This is a textbook designed for an advanced course in control theory. Currently most textbooks on the subject either looks at "multivariate" systems or "non-linear" systems. However, Control Theory is the only textbook available that covers both. It explains current developments in these two types of control techniques, and looks at tools for computer-aided design, for example Matlab and its toolboxes. To make full use of computer design tools, a good understanding of their theoretical basis is necessary, and to enable this, the book presents relevant mathematics clearly and simply. The practical limits of control systems are explored, and the relevance of these to control design are discussed. Control Theory is an ideal textbook for final-year undergraduate and postgraduate courses, and the student will be helped by a series of exercises at the end of each chapter. Professional engineers will also welcome it as a core reference.
Modeling of Dynamic Systems
Written by a recognized authority in the field of identification and control, this book draws together into a single volume the important aspects of system identification AND physical modelling. KEY TOPICS: Explores techniques used to construct mathematical models of systems based on knowledge from physics, chemistry, biology, etc. (e.g., techniques with so called bond-graphs, as well those which use computer algebra for the modeling work). Explains system identification techniques used to infer knowledge about the behavior of dynamic systems based on observations of the various input and output signals that are available for measurement. Shows how both types of techniques need to be applied in any given practical modeling situation. Considers applications, primarily simulation. MARKET: For practicing engineers who are faced with problems of modeling.
Signal Analysis and Prediction
Methods of signal analysis represent a broad research topic with applications in many disciplines, including engineering, technology, biomedicine, seismography, eco nometrics, and many others based upon the processing of observed variables. Even though these applications are widely different, the mathematical background be hind them is similar and includes the use of the discrete Fourier transform and z-transform for signal analysis, and both linear and non-linear methods for signal identification, modelling, prediction, segmentation, and classification. These meth ods are in many cases closely related to optimization problems, statistical methods, and artificial neural networks. This book i...
The Secret War Against Sweden
Ola Tunander's revelations make it clear that the United States and Britain ran a "secret war" in Swedish waters.
Fuzzy Modeling for Control
Rule-based fuzzy modeling has been recognised as a powerful technique for the modeling of partly-known nonlinear systems. Fuzzy models can effectively integrate information from different sources, such as physical laws, empirical models, measurements and heuristics. Application areas of fuzzy models include prediction, decision support, system analysis, control design, etc. Fuzzy Modeling for Control addresses fuzzy modeling from the systems and control engineering points of view. It focuses on the selection of appropriate model structures, on the acquisition of dynamic fuzzy models from process measurements (fuzzy identification), and on the design of nonlinear controllers based on fuzzy mo...
