Bounding Approaches to System Identification
M. Milanese (Editor), J. Norton (Editor), H. Piet-LahanierBooks.org participates in affiliate programs including Bookshop.org and the Amazon Services LLC Associates Program. We may earn a commission from qualifying purchases made through links on this page, at no additional cost to you.
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.Synopsis
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.
Booknews
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)