Switching and Learning in Feedback Systems反馈系统的交换与学习/会议录

出版社:1 (2005年3月24日)
出版日期:2005-3
ISBN:9783540244578
作者:Roderick Murray-Smith
页数:342页

书籍目录

Switching and Control From Feedback Control to Complexity Management: A Personal Perspective Convex Cones, Lyapunov Functions, and the Stability of Switched Linear Systems Survey of Explicit Approaches to Constrained Optimal Control Gaussian Processes Analysis of Some Methods for Reduced Rank Gaussian Process Regression Filtered Gaussian Processes for Learning with Large Data-Sets Self-tuning Control of Non-linear Systems Using Gaussian Process Prior Models Gaussian Processes: Prediction at a Noisy Input and Application to Iterative Multiple-Step Ahead  Forecasting of Time-Series  Nonlinear Predictive Control with a Gaussian Process ModelApplications of Switching & Learning Control of Yaw Rate and Sideslip in 4-Wheel Steering Cars with Actuator ConstraintsA Second-Order Cone Bounding Algorithm for Robust Minimum Joint Optimization of Wireless Communication and Networked Control Systems   Reconciliation of Inconsistencies in the Theory of Linear Systems  An Introduction to Nonparametric Hierarchical Bayesian Modelling with a Focus on Multi-agent Learning Simultaneous Localization and Surveying with Multiple Agents Hex: Dynamics and Probabilistic Text EntryAuthor Index

作者简介

This book presents the outcome of the European Summer School on Multi-agent Control, held in Maynooth, Ireland in September 2003.  The past decade witnessed remarkable progress in the area of dynamic systems with the emergence of a number of powerful methods for both modeling and controlling uncertain dynamic systems. The first two parts of this book present tutorial lectures by leading researchers in the area introducing the reader to recent achievements on switching and control and on Gaussian processes. The third part is devoted to the presentation of original research contributions in the area; among the topics addressed are car control, bounding algorithms, networked control systems, the theory of linear systems, Bayesian modeling, and surveying multiagent systems.


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