Overview

An exposition of the interplay between the modelling of dynamic systems and the design of feedback controllers based on these models is the main goal of this book. The combination of both subjects into a cohesive development allows the consistent treatment of both problems to yield powerful new tools for the improvement of system performance. Central among the themes of this work is the observation that operation of a system in feedback with a controller exposes the areas in which the model fit is constraining the controller performance achieved. The book presents new techniques for the understanding of the iterative improvement of performance through the successive fitting of models using closed-loop data and the design of high-performance controllers using these models. The subject matter includes: New approaches to understanding how to affect the fit of dynamical models to physical processes through the choice of experiments, data pre-filtering and model structure; connections between robust control design methods and their dependency on the quality of model fit; experimental design in which data collected in operation under feedback can reveal areas that limit the performance achieved; iterative approaches to link these model-fitting and control design phases in a cogent manner so as to achieve improved performance overall. The authors of individual chapters are some of the most renowned and authoritative figures in the fields of system identification and control design.

Full Product Details

Author:   Pedro Albertos ,  Antonio Sala Piqueras
Publisher:   Springer London Ltd
Imprint:   Springer London Ltd
Dimensions:   Width: 15.50cm , Height: 1.90cm , Length: 23.50cm
Weight:   0.700kg
ISBN:  

9781852335090

ISBN 10:   1852335092
Pages:   309
Publication Date:   21 May 2002
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   Awaiting stock  
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Table of Contents

I. Fundamentals and Theory.- 1 Modelling, Identification and Control.- 1.1 A not-so-brief Historical Perspective.- 1.2 A Typical Scenario and its Major Players.- 1.3 Some Important New Insights.- 2 System Identification. Performance and Closed-loop Issues.- 2.1 Chapter Outline.- 2.2 Modelling, Estimation and Identification.- 2.3 Model Structures.- 2.4 Implementation of the Model Structures: Predictors.- 2.5 Open-loop Identification. What can be Achieved?.- 2.6 Open-loop Identification Algorithms.- 2.7 Closed-loop Identification.- 3 Data Preparation for Identification.- 3.1 Introduction.- 3.2 Design Variables for Identification.- 3.3 Data Preparation: Detrending and Filtering.- 3.4 System Identification with an H? Criterion.- 3.5 Conclusions.- 4 Model Uncertainty and Feedback.- 4.1 Introduction.- 4.2 Classical Control Theory.- 4.3 State-space Theory.- 4.4 Fundamental Limitations.- 4.5 H? Loop Shaping.- 4.6 Summary.- 5 Open-loop Iterative Learning Control.- 5.1 Introduction.- 5.2 Control with Two Degrees of Freedom.- 5.3 The Iterative Learning Paradigm.- 5.4 The Learning Algorithms.- 5.5 Examples.- 5.6 Conclusions.- 6 Model-based Iterative Control Design.- 6.1 Introduction.- 6.2 Iterative Control Design.- 6.3 Application 1: Single Control Loop.- 6.4 Application 2: GPC Control Approach.- 6.5 Conclusions.- 7 Windsurfing Approach to Iterative Control Design.- 7.1 Introduction.- 7.2 Fundamental Problems in Adaptive Control.- 7.3 High-level Overview of the Windsurfer Approach to Adaptive Control.- 7.4 More Detailed Description of the Algorithm.- 7.5 Examples.- 7.6 Unstable Plants.- 7.7 Coping with the “Fundamental Problems”.- 7.8 Some Further Quantitative Directions.- 8 Iterative Optimal Control Design.- 8.1 Introduction.- 8.2 Controller Tuning with Data.- 8.3 Iterative Identification and Control Design.- 8.4 Introducing Caution into Iterative Design.- 8.5 Embellishments and Conclusion.- 9 Identification and Validation for Robust Control.- 9.1 Introduction.- 9.2 The Identification/Control Setup and some Basic Formulae.- 9.3 A Control-oriented Nominal Model.- 9.4 Caution in Iterative Design.- 9.5 Model Validation for Robust Control Design.- 9.6 Conclusions.- II. Applications.- 10 Helicopter Vibration Control.- 10.1 Helicopter Vibration Control Example.- 10.2 A Glimpse of the Solution.- 10.3 Modelling Requirements.- 10.4 Identification Experiments.- 10.5 Data Analysis and Sanitizing.- 10.6 Parametric System Identification.- 10.7 Conclusions.- 11 Control-relevant Identification and Servo Design for a Compact Disc Player.- 11.1 Introduction.- 11.2 The Compact Disc Mechanism.- 11.3 Control-relevant Modelling of Radial Actuator.- 11.4 Preliminaries and Notations.- 11.5 Common Objectives in Identification and Control.- 11.6 Estimation of Coprime Factorisations.- 11.7 Application to CD Radial Actuator.- 11.8 Control Design and Stability Robustness.- 11.9 Summary.- 12 Control-relevant Identification and Robust Motion Control of a Wafer Stage.- 12.1 Introduction.- 12.2 The Wafer Stepper Positioning Mechanism.- 12.3 Iterative Model Set Estimation and Control Design.- 12.4 Elements of the Iterative Scheme.- 12.5 Estimation of Model Set for the Wafer Stage.- 12.6 Model Set-based Robust Control Design.- 12.7 Summary.- 13 Iterative Identification and Control: a Sugar Cane Crushing Mill.- 13.1 Introduction.- 13.2 The Sugar Cane Crushing Process.- 13.3 Identification Procedure.- 13.4 Controller Design.- 13.5 Iterative Approach.- 13.6 Conclusions.

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