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Catalogue : Details

Timm Faulwasser

Optimization-based Solutions to Constrained Trajectory-tracking and Path-following Problems

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ISBN:978-3-8440-1594-2
Series:Contributions in Systems Theory and Automatic Control, Otto-von-Guericke-Universität Magdeburg
Herausgeber: Otto-von-Guericke Universität Magdeburg and Institut für Automatisierungstechnik
Magdeburg
Volume:3
Keywords:Regelungstechnik; prädiktive Regelung; Pfadverfolgung; nonlinear model predictive control; path following; trajectory tracking
Type of publication:Thesis
Language:English
Pages:184 pages
Figures:23 figures
Weight:272 g
Format:21 x 14,8 cm
Binding:Paperback
Price:35,80 € / 44,75 SFr
Published:January 2013
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DOI:10.2370/9783844015942 (Online document)
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Abstract:The prototypical problem in control theory is the stabilization of a set point. When, instead of a set point, a time-varying reference needs to be stabilized, then the problem is called trajectory tracking. Typical examples of trajectory-tracking problems are set point changes along precomputed references, synchronization tasks or startup of processes. While stabilization and trajectory tracking are well-understood for a wide range of systems, not all control tasks arising in practice belong to these categories. In robotics, for example, it is frequently required to move a robot along a geometric curve without any preassigned timing information. In other words, the speed to move along the curve is a degree of freedom. Such problems are called path-following problems. This book deals with nonlinear model predictive control (NMPC) for constrained trajectory-tracking and path-following problems. Based on a detailed problem analysis a framework to tackle these problems is developed. Examples from robotics and chemical engineering are used to illustrate the results. The main concerns of this book are twofold: On the one hand, it is shown that nonlinear model predictive control is very well applicable to problems beyond set point stabilization. On the other hand, it is demonstrated that path-following concepts provide a suitable framework for many challenging control problems ranging from robotics to chemical engineering.