Robustness in Identification and Control

Author:   Andrea Garulli ,  Alberto Tesi ,  Antonio Vicino ,  Antonio Vicino (Professor, Dipartimento di Ingegneria dell'Informazione, Universita di Siena, Italy)
Publisher:   Springer London Ltd
Edition:   Edition. ed.
Volume:   245
ISBN:  

9781852331795


Pages:   471
Publication Date:   11 June 1999
Format:   Paperback
Availability:   Out of stock   Availability explained
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Robustness in Identification and Control


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Overview

This is a selection of papers that were first presented at the Robustness in Identification and Control Workshop, held in Siena, July 30 - August 2, 1998. The common theme underlying all of the contributions is the interplay between information, uncertainty and complexity in dealing with modelling, identification and control of dynamical systems. Papers cover developments in research areas such as identification for control and the classical area of robust control. There are a number of real-world case studies where the most advanced robustness analysis and synthesis techniques are applied to resolve previously unsolved problems.

Full Product Details

Author:   Andrea Garulli ,  Alberto Tesi ,  Antonio Vicino ,  Antonio Vicino (Professor, Dipartimento di Ingegneria dell'Informazione, Universita di Siena, Italy)
Publisher:   Springer London Ltd
Imprint:   Springer London Ltd
Edition:   Edition. ed.
Volume:   245
Dimensions:   Width: 15.50cm , Height: 2.50cm , Length: 23.50cm
Weight:   0.741kg
ISBN:  

9781852331795


ISBN 10:   1852331798
Pages:   471
Publication Date:   11 June 1999
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Out of stock   Availability explained
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

Table of Contents

Robustness in identification.- Comments on model validation as set membership identification.- SM identification of model sets for robust control design from data.- Robust identification and the rejection of outliers.- Semi-parametric methods for system identification.- Modal robust state estimator with deterministic specification of uncertainty.- The role of experimental conditions in model validation for control.- Modeling and validation of nonlinear feedback systems.- Towards a harmonic blending of deterministic and stochastic frameworks in information processing.- Suboptimal conditional estimators for restricted complexity set membership identification.- Worst-case simulation of uncertain systems.- On performance limitations in estimation.- Design criteria for uncertain models with structured and unstructured uncertainties.- Robustness and performance in adaptive filtering.- Nonlinear identification based on unreliable priors and data, with application to robot localization.- Robust model predictive control: A survey.- Intrinsic performance limits of linear feedback control.- Puzzles in systems and control.- Robust regional pole placement: An affine approximation.- On achieving L p (?p) performance with global internal stability for linear plants with saturating actuators.- Control under structural constraints: An input-output approach.- Multi-objective MIMO optimal control design without zero interpolation.- Robustness synthesis in l 1: A globally optimal solution.- Optimal control of distributed arrays with spatial invariance.- Numerical search of stable or unstable element in matrix or polynomial families: A unified approach to robustness analysis and stabilization.- A convex approach to a class of minimum norm problems.- Quantified inequalities and robust control.- Dynamic programming for robust control: Old ideas and recent developments.- Robustness of receding horizon control for nonlinear discrete-time systems.- Nonlinear representations and passivity conditions in discrete time.- Robust ripple-free output regulation and tracking under structured or unstructured parameter uncertainties.- An experimental study of performance and fault-tolerance of a hybrid free-flight control scheme.

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