Adaptive Control
Published on 21. September 2012
Book
Paperback/Softback
XX, 562 pages
978-1-4471-1044-6 (ISBN)
Description
Ad ap tive Contro l provid es tec hniques for aut omatic adjustment in real t ime of cont roller parameter s in order to achieve or to maintain a desired level for the performance of cont rol systems when the dyn amic param et ers of t he process are unknown and/or var y in time. These techniques have as a main feature t he abilit y to ext ract significant information from real dat a in ord er to tune the cont roller and they feature a me chanism for adjust ing parameter s (of a plant model or of a cont roller). While the history of Adaptive Control is lon g, significant progr ess in under - standing and applying Adaptive Con trol began in the early sevent ies. The growing availability of digital com puters have also contributed to the devel- opment of the field . The earlier applicat ions in the sevent ies and beginning of the eight ies, provided important feedback for the development of the field . Theoretical developments allowed a number of basic problems to be solved . The aim of this book is to provide a coherent and comprehensive treatment of the field .
The presentation takes the read er from the basic problem formu- lation to the analytical solutions who se prac tical significance is illustrated by applications.
The presentation takes the read er from the basic problem formu- lation to the analytical solutions who se prac tical significance is illustrated by applications.
Reviews / Votes
From the reviews:
In conclusion, I found this book well written, interesting and easy to follow, so that it constitutes a valuable addition to the existing monographies in adaptive control for discrete-time linear systems. Moreover, the organization of the book makes it suitable (at least in part) for use in graduate courses in adaptive control.
Automatica 38 (2002) 1093 - 1094 (Reviewer: Patrizio Tomei)
More details
Series
Edition
Softcover reprint of the original 1st ed. 1998
Language
English
Place of publication
London
United Kingdom
Target group
Professional and scholarly
Research
Illustrations
XX, 562 p.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 32 mm
Weight
873 gr
ISBN-13
978-1-4471-1044-6 (9781447110446)
DOI
10.1007/978-0-85729-343-5
Schweitzer Classification
Other editions
Additional editions
Person
Bernard Brogliato was born in 1963, graduated from Ecole Normale Supérieure de Cachan (France), Mechanical Engineering Dept., Ph.D. and Habilitation degree in Automatic Control from Grenoble Institute of Technology ¿in 1991¿and 1995 respectively. He is Senior Researcher at INRIA Grenoble Rhône-Alpes. Research interests: non-smooth dynamical systems (analysis, control and observation, numerics), impact and contact mechanics, digital sliding-mode control. Wrote about 90 articles in international journals in the fields of Systems and Control, Mechanical Engineering, and Applied Mathematics. Also authored and co-authored five monographs. He was Associate Editor for Automatica (1999-2008), is Associate Editor for Nonlinear Analysis Hybrid Systems, and ASME Journal of Computational and Nonlinear Dynamics.
Rogelio Lozano was born in Monterrey Mexico, on July 12, 1954. He received the B.S. degree in electronic engineering fromthe National Polytechnic Institute of Mexico in 1975, the M.S. degree in electrical engineering from Centro de Investigación y de Estudios Avanzados (CINVESTAV), Mexico in 1977, and the Ph.D. degree in automatic control from Laboratoire d'Automatique de Grenoble, France, in 1981. He joined the Department of Electrical Engineering at CINVESTAV, Mexico, in 1981 where he worked until 1989. He was Head of the Section of Automatic Control from June 1985 to August 1987. He has held visiting positions at the University of Newcastle, Australia, from November 1983 to November 1984, NASA Langley Research Center VA, from August 1987 to August 1988, and Laboratoire d'Automatique de Grenoble, France, from February 1989 to July 1990. Since 1990 he is a CNRS (Centre National de la Recherche Scientifique) Research Director at University of Technology of Compiègne, France. He was Associate Editor of Automatica in the period 1987-2000. He is associate Editor of the Journal of Intelligentand Robotics Systems since 2012 and Associate Editor in the Int. J. of Adaptive Control and Signal Processing since 1988.
Bernhard Maschke is Professor of Automatic Control of the University Claude Bernard of Lyon, Villeurbanne, France since 2000. The main streamline of his research is the nonlinear and passivity-based control of complex physical systems. He is one of the main initiators of the Port Hamiltonian formalism which bases the modelling, simulation and control of complex physical systems on network theory and thermodynamic theory. He has used this formalism for complex spatial mechanisms and in the mechatronic context of automotive applications and more recently to chemical enginneering processes and various multi-physics and multi-scale systems such as an adsorption process, a fuel cell or an Ion Polymer Metal Composite.
Olav Egeland is a graduate of the Norwegian University of Science and Technology (NTNU), where he is professor of production automation. He was at Marine Cybernetics AS 2004-2011 as co-founder. He has received the Automatica Prize Paper Award and the Outstanding Paper Award of IEEE Trans. Control Systems Technology, and has been Associate Editor of IEEE Trans. Automatic Control and European Journal of Control. His research is on modelling, simulation and control of mechanical systems with applications to robotics and offshore systems.
Content
to Adaptive Control.- Adaptive Control - Why?.- Adaptive Control Versus Conventional Feedback Control.- Basic Adaptive Control Schemes.- Examples.- A Brief Historical Note.- Concluding Remarks.- Discrete Time System Models for Control.- Deterministic Environment.- Stochastic Environment.- Concluding Remarks.- Problems.- Parameter Adaptation Algorithms - Deterministic Environment.- The Problem.- PAA - Examples.- Stability of Parameter Adaptation Algorithms.- Parametric Convergence.- Concluding Remarks.- Problems.- Parameter Adaptation Algorithms - Stochastic Environment.- Effect of Stochastic Disturbances.- The Averaging Method.- The Martingale Approach.- The Frequency Domain Approach.- Concluding Remarks.- Problems.- Recursive Plant Model Identification in Open Loop.- Recursive Identification in the Context of System Identification.- Structure of Recursive Parameter Estimation Algorithms.- Identification Methods (Type I).- Validation of the Models Identified with Type I Methods.- Identification Methods (Type II).- Validation of the Models Identified with Type II Methods.- Selection of the Pseudo Random Binary Sequence.- Model Order Selection.- An Example: Identification of a Flexible Transmission.- Concluding Remarks.- Problems.- Adaptive Prediction.- The Problem.- Adaptive Prediction - Deterministic Case.- Adaptive Prediction - Stochastic Case.- Concluding Remarks.- Problems.- Digital Control Strategies.- Canonical Form for Digital Controllers.- Pole Placement.- Tracking and Regulation with Independent Objectives.- Tracking and Regulation with Weighted Input.- Minimum Variance Tracking and Regulation.- Generalized Predictive Control.- Linear Quadratic Control.- Concluding Remarks.- Problems.- Robust Digital Control Design.- The Robustness Problem.- The Sensitivity Functions.- Robust Stability.- Definition of "Templates" for the Sensitivity Functions.- Properties of the Sensitivity Functions.- Shaping the Sensitivity Functions.- Example: Robust Digital Control of a Flexible Transmission.- Concluding Remarks.- Problems.- Recursive Plant Model Identification in Closed Loop.- The Problem.- Closed Loop Output Error Algorithms.- Filtered Open Loop Recursive Identification Algorithms.- Frequency Distribution of the Asymptotic Bias in Closed Loop Identification.- Validation of Models Identified in Closed Loop.- Comparative Evaluation of the Various Algorithms.- Concluding Remarks.- Problems.- Robust Parameter Estimation.- The Problem.- Input/Output Data Filtering.- Effect of Disturbances.- PAA with Dead Zone.- PAA with Projection.- Data Normalization.- A Robust Parameter Estimation Scheme.- Concluding Remarks.- Problems.- Direct Adaptive Control.- Adaptive Tracking and Regulation with Independent Objectives.- Adaptive Tracking and Regulation with Weighted Input.- Adaptive Minimum Variance Tracking and Regulation.- Adaptive Generalized Minimum Variance Control.- Robust Direct Adaptive Control.- An example.- Concluding Remarks.- Problems.- Indirect Adaptive Control.- Adaptive Pole Placement.- Robust Indirect Adaptive Control.- Adaptive Generalized Predictive Control.- Adaptive Linear Quadratic Control.- Iterative Identification in Closed Loop and Controller Redesign.- An Example.- Concluding Remarks.- Practical Aspects and Applications.- The Digital Control System.- The Parameter Adaptation Algorithm.- Adaptive Control Algorithms.- Initialization of Adaptive Control Schemes.- Supervision.- Iterative Identification in Closed Loop and Controller Redesign.- Adaptive Tracking and Robust Regulation.- Indirect Adaptive Control.- ConcludingRemarks.- A Perspective View and Further Reading.- Stochastic Processes.- Stability.- Passive (Hyperstable) Systems.- Passive (Hyperstable) Systems.- Passivity - Some Definitions.- Discrete Linear Time-Invariant Passive Systems.- Discrete Linear Time-Varying Passive Systems.- Stability of Feedback Interconnected Systems.- Hyperstability and Small Gain.- Martingales.