Del i serien Communications and Control Engineering

Adaptive Control

Häftad, Engelska, 2012

AvRogelio Lozano

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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.

Produktinformation

Utgivningsdatum2012-09-21
Mått155 x 235 x 32 mm
Vikt873 g
FormatHäftad
SpråkEngelska
SerieCommunications and Control Engineering
Antal sidor562
FörlagSpringer London Ltd
ISBN9781447110446

Tillhör följande kategorier

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.

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)