Ebook: Iterative Identification and Control: Advances in Theory and Applications

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.

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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.

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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.
Content:
Front Matter....Pages i-xvii
Front Matter....Pages 1-1
Modelling, Identification and Control....Pages 3-16
System Identification. Performance and Closed-loop Issues....Pages 17-40
Data Preparation for Identification....Pages 41-62
Model Uncertainty and Feedback....Pages 63-97
Open-loop Iterative Learning Control....Pages 99-119
Model-based Iterative Control Design....Pages 121-142
Windsurfing Approach to Iterative Control Design....Pages 143-166
Iterative Optimal Control Design....Pages 167-184
Identification and Validation for Robust Control....Pages 185-208
Front Matter....Pages 209-209
Helicopter Vibration Control....Pages 211-223
Control-relevant Identification and Servo Design for a Compact Disc Player....Pages 225-242
Control-relevant Identification and Robust Motion Control of a Wafer Stage....Pages 243-270
Iterative Identification and Control: A Sugar Cane Crushing Mill....Pages 271-295
Back Matter....Pages 297-309

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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.
Content:
Front Matter....Pages i-xvii
Front Matter....Pages 1-1
Modelling, Identification and Control....Pages 3-16
System Identification. Performance and Closed-loop Issues....Pages 17-40
Data Preparation for Identification....Pages 41-62
Model Uncertainty and Feedback....Pages 63-97
Open-loop Iterative Learning Control....Pages 99-119
Model-based Iterative Control Design....Pages 121-142
Windsurfing Approach to Iterative Control Design....Pages 143-166
Iterative Optimal Control Design....Pages 167-184
Identification and Validation for Robust Control....Pages 185-208
Front Matter....Pages 209-209
Helicopter Vibration Control....Pages 211-223
Control-relevant Identification and Servo Design for a Compact Disc Player....Pages 225-242
Control-relevant Identification and Robust Motion Control of a Wafer Stage....Pages 243-270
Iterative Identification and Control: A Sugar Cane Crushing Mill....Pages 271-295
Back Matter....Pages 297-309
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