Bounding Approaches to System Identification

by M. Milanese (Editor), J. Norton (Editor), H. Piet-Lahanier (Editor), ï. Walter (Editor)

Overview

In response to the growing interest in bounding error approaches, the editors of this volume offer the first collection of papers to describe advances in techniques and applications of bounding of the parameters, or state variables, of uncertain dynamical systems. Contributors explore the application of the bounding approach as an alternative to the probabilistic analysis of such systems, relating its importance to robust control-system design.

Product Details

ISBN-13:	9781475795479
Publisher:	Springer US
Publication date:	05/05/2013
Edition description:	Softcover reprint of the original 1st ed. 1996
Pages:	567
Product dimensions:	5.98(w) x 9.02(h) x 0.05(d)

Table of Contents

1. Overview of the Volume.- 2. Optimal Estimation Theory for Dynamic Systems with Set Membership Uncertainty: An Overview.- 3. Solving Linear Problems in the Presence of Bounded Data Perturbations.- 4. Review and Comparison of Ellipsoidal Bounding Algorithms.- 5. The Dead Zone in System Identification.- 6. Recursive Estimation Algorithms for Linear Models with Set Membership Error.- 7. Transfer Function Parameter Interval Estimation Using Recursive Least Squares in the Time and Frequency Domains.- 8. Volume-Optimal Inner and Outer Ellipsoids.- 9. Linear Interpolation and Estimation Using Interval Analysis.- 10. Adaptive Approximation of Uncertainty Sets for Linear Regression Models.- 11. Worst-Case l1 Identification.- 12. Recursive Robust Minimax Estimation.- 13. Robustness to Outliers of Bounded-Error Estimators and Consequences on Experiment Design.- 14. Ellipsoidal State Estimation for Uncertain Dynamical Systems.- 15. Set-Valued Estimation of State and Parameter Vectors within Adaptive Control Systems.- 16. Limited-Complexity Polyhedric Tracking.- 17. Parameter-Bounding Algorithms for Linear Errors-in-Variables Models.- 18. Errors-in-Variables Models in Parameter Bounding.- 19. Identification of Linear Objects with Bounded Disturbances in Both Input and Output Channels.- 20. Identification of Nonlinear State-Space Models by Deterministic Search.- 21. Robust Identification and Prediction for Nonlinear State-Space Models with Bounded Output Error.- 22. Estimation Theory for Nonlinear Models and Set Membership Uncertainty.- 23. Guaranteed Nonlinear Set Estimation via Interval Analysis.- 24. Adaptive Control of Systems Subjected to Bounded Disturbances.- 25. Predictive Self-Tuning Control by Parameter Bounding and Worst-Case Design.- 26. System Identification forH?-Robust Control Design.- 27. Estimation of Mobile Robot Localization: Geometric Approaches.- 28. Improved Image Compression Using Bounded-Error Parameter Estimation Concepts.- 29. Applications of OBE Algorithms to Speech Processing.- 30. Robust Performances Control Design for a High Accuracy Calibration Device.

Editorial Reviews

‘A comprehensive and modern overview.'
Mathematical Reviews

From the Publisher

The appeal of bounding lies in its directness, simplicity, and need for few assumptions compared with its probabilistic alternatives; its ability to make use of prior knowledge expressed as bounds; and its status as the natural basis for worst case design. Thirty contributed chapters consider various aspects of both linear and nonlinear models as well as various facets of bounding in robust/adaptive control, and applications of parameter bounding in areas as diverse as robotics, image compression, speech processing, and high-accuracy calibration. Annotation c. Book News, Inc., Portland, OR (booknews.com)

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