Skip to main content
SpringerLink
Log in

Switching and Learning in Feedback Systems

European Summer School on Multi-Agent Control, Maynooth, Ireland, September 8-10, 2003, Revised Lectures and Selected Papers

  • Book
  • © 2005

Overview

Editors:
  1. Roderick Murray-Smith

    1. Hamilton Institute, NUI Maynooth, Ireland

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Robert Shorten

    1. Hamilton Institute, NUIM, Ireland

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 3355)

Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (15 chapters)

  1. Front Matter

    Download chapter PDF

  2. Switching and Control

    1. From Feedback Control to Complexity Management: A Personal Perspective

      • Kumpati S. Narendra
      Pages 1-30

    2. Convex Cones, Lyapunov Functions, and the Stability of Switched Linear Systems

      • Robert Shorten, Oliver Mason, Kai Wulff
      Pages 31-46

    3. Survey of Explicit Approaches to Constrained Optimal Control

      • Alexandra Grancharova, Tor Arne Johansen
      Pages 47-97

  3. Gaussian Processes

    1. Analysis of Some Methods for Reduced Rank Gaussian Process Regression

      • Joaquin Quiñonero-Candela, Carl Edward Rasmussen
      Pages 98-127

    2. Filtered Gaussian Processes for Learning with Large Data-Sets

      • Jian Qing Shi, Roderick Murray-Smith, D. Mike Titterington, Barak A. Pearlmutter
      Pages 128-139

    3. Self-tuning Control of Non-linear Systems Using Gaussian Process Prior Models

      • Daniel Sbarbaro, Roderick Murray-Smith
      Pages 140-157

    4. Gaussian Processes: Prediction at a Noisy Input and Application to Iterative Multiple-Step Ahead Forecasting of Time-Series

      • Agathe Girard, Roderick Murray-Smith
      Pages 158-184

    5. Nonlinear Predictive Control with a Gaussian Process Model

      • Juš Kocijan, Roderick Murray-Smith
      Pages 185-200

  4. Applications of Switching & Learning

    1. Control of Yaw Rate and Sideslip in 4-Wheel Steering Cars with Actuator Constraints

      • Miguel A. Vilaplana, Oliver Mason, Douglas J. Leith, William E. Leithead
      Pages 201-222

    2. A Second-Order Cone Bounding Algorithm for Robust Minimum Variance Beamforming

      • Ngai Wong, Venkataramanan Balakrishnan, Tung-Sang Ng
      Pages 223-247

    3. Joint Optimization of Wireless Communication and Networked Control Systems

      • Lin Xiao, Mikael Johansson, Haitham Hindi, Stephen Boyd, Andrea Goldsmith
      Pages 248-272

    4. Reconciliation of Inconsistencies in the Theory of Linear Systems

      • Emanuele Ragnoli, William Leithead
      Pages 273-289

    5. An Introduction to Nonparametric Hierarchical Bayesian Modelling with a Focus on Multi-agent Learning

      • Volker Tresp, Kai Yu
      Pages 290-312

    6. Simultaneous Localization and Surveying with Multiple Agents

      • Sam T. Roweis, Ruslan R. Salakhutdinov
      Pages 313-332

    7. Hex: Dynamics and Probabilistic Text Entry

      • John Williamson, Roderick Murray-Smith
      Pages 333-342

  5. Back Matter

    Download chapter PDF
Back to top

Keywords

About this book

A central theme in the study of dynamic systems is the modelling and control of uncertain systems. While ‘uncertainty’ has long been a strong motivating factor behind many techniques developed in the modelling, control, statistics and mathematics communities, the past decade, in particular, has witnessed remarkable progress in this area with the emergence of a number of powerful newmethodsforbothmodellingandcontrollinguncertaindynamicsystems. The speci?c objective of this book is to describe and review some of these exciting new approaches within a single volume. Our approach was to invite some of the leading researchers in this area to contribute to this book by submitting both tutorial papers on their speci?c area of research, and to submit more focussed research papers to document some of the latest results in the area. We feel that collecting some of the main results together in this manner is particularly important as many of the important ideas that emerged in the past decade were derived in a variety of academic disciplines. By providing both tutorial and researchpaperswehopetobeabletoprovidetheinterestedreaderwithsu?cient background to appreciate some of the main concepts from a variety of related, but nevertheless distinct ?elds, and to provide a ?avor of how these results are currently being used to cope with ‘uncertainty. ’ It is our sincere hope that the availability of these results within a single volume will lead to further cro- fertilization of ideas and act as a spark for further research in this important area of applied mathematics.

Editors and Affiliations

  • Hamilton Institute, NUI Maynooth, Ireland

    Roderick Murray-Smith

  • Hamilton Institute, NUIM, Ireland

    Robert Shorten

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation