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Analysis and control of nonlinear process systems
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Berlin : Springer, 2004


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30000004615922 TS156.8 H34 2004 Open Access Book Book

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This straightforward text makes the complicated but powerful methods of non-linear control accessible to process engineers. Not only does it cover the necessary mathematics, but it consistently refers to the widely-known finite-dimensional linear time-invariant continuous case as a basis for extension to the nonlinear situation.

Author Notes

Katalin Hangos obtained M.Sc.s in chemistry and computer science form Loránd Eötvös University in Budapest, and a Ph.D. and D.Sc from the Hungarian Academy of Science. She is currently a professor at the Hungarian Academy as well as a visiting professor at the University of Queensland and at the Technical University of Denmark. Her current research interests include: intelligent control systems and the theoretical foundations of model-based operator support systems. She teaches at both undergraduate and postgraduate level in intelligent control and the analysis and control of non-linear systems.

József Bokor is the Research Director of the Systems and Control Laboratory at the Hungarian Academy of Sciences. He obtained his M.Sc. from the Technical University of Budapest and his Ph.D. and D.Sc. from the Hungarian Academy. His research interests include Identification problems in closed-loop systems, fault detection and modelling of dynamic systems with associated realisation theories. He teaches postgraduate courses in multi-variable feedback systems, system identification and control of non-linear systems.

Gábor Szederkényi has just obtained his Ph.D. from the University of Veszprém but has already published papers in a number of peer-reviewed journals and is now a research fellow at the Hungarian Academy. His research interests include: analysis and control of non-linear systems and model-based fault detection and diagnosis in non-linear systems. He currently teaches undergraduates in linear control theory and discrete mathematics.

Table of Contents

Basic Notions of Systems and Signals
State-space Models
Dynamic Process Models
Input-output Models and Realization Theory
Controllability and Observability
Stability and the Lyapunov Method
Passivity and the Hamiltonian View
State Feedback Controllers
Feedback and Input-Output Linearization of Nonlinear Systems
Passivation by Feedback
Stabilization and Loop Shaping
Appendix: Mathematical Preliminaries