Digital Self-tuning Controllers
Algorithms, Implementation and Applications
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Beschreibung
Adaptive control theory has developed significantly over the past few years; self-tuning control represents one branch of adaptive control that has been successfully applied in practice. Controller design requires knowledge of the plant to be controlled which is not always readily accessible; self-tuning controllers gather such information during normal operation and adjust controller designs on-line as required.
Digital Self-tuning Controllers presents you with a complete course in self-tuning control, beginning with a survey of adaptive control and the formulation of adaptive control problems. Modelling and identification are dealt with before passing on to algebraic design methods and particular PID and linear-quadratic forms of self-tuning control. Finally, laboratory verification and experimentation will show you how to ground your theoretical knowledge in real plant control.
Features:
• comprehensive coverage providing everything a student needs to know about self-tuning control from literature survey to the control of an experimental heat exchanger;
• a strong emphasis on practical problem solving with control algorithms clearly laid out in easy-to-follow formulae or made directly available as Matlab® functions making the book particularly suitable as an aid to project work;
• specially written MATLAB® toolboxes convenient for the presentation of typical control system and plant properties and ready for use in direct control of real or simulated plants available from springeronline.com;
• worked examples and tutorial exercises to guide you through the learning process.
Digital Self-tuning Controllers comprises an invaluable course with which graduate students and advanced undergraduates can learn how to overcome the significant problems of putting the powerful tools of adaptive control theory into practice. The textwill also be of much interest to control engineers wishing to employ the ideas of adaptive control in their designs and plant.
Adaptive control theory has developed significantly over the past few years; self-tuning control represents one branch of adaptive control that has been successfully applied in practice. This book presents a complete course in self-tuning control. It gives comprehensive coverage, featuring a strong emphasis on practical problem solving, with control algorithms clearly laid out in easy-to-follow formulae, code listings or made directly available as MATLAB® functions, making the book particularly suitable as an aid to project work. Specially written MATLAB® toolboxes are available, plus worked examples and tutorial exercises at every stage of the learning process.
Practical emphasis to teach students to use the powerful ideas of adaptive control in real applications Custom-made Matlab® functionality to facilitate the design and construction of self-tuning controllers for different processes and systems Examples, tutorial exercises and clearly laid-out flowcharts and formulae to make the subject simple to follow for students and to help tutors with class preparation Includes supplementary material: sn.pub/extras
Autor*in
Vladimír Bobál
Themen in »Digital Self-tuning Controllers«
Adaptive Control Automatic Control Control Control Engineering Digital Control Linear Quadratic Control MATLAB Normal Recursive Least Squares Self-tuning Control Simulink process integration
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From the reviews:
"The monograph under review tries to systematically cover all these aspects for one class of adaptive control systems, namely self-tuning systems. … The book is an excellent complete course on self-tuning and adaptive control systems based on the plant on-line identification. It can be very useful for practically oriented control engineers wanted to employ the ideas of self-tuning control on real industrial plants. … Also researches developing new methods for design and simulation of adaptive control systems may find here some interesting ideas." (Boris Rohal-Ilkiv, International Journal of Robust and Nonlinear Control, Vol. 17, 2007)
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