Distributed Control of Robotic Networks
by Francesco Bullo, Jorge Cortes, Sonia Martinez
Publisher: Princeton University Press 2009
Number of pages: 323
This self-contained introduction to the distributed control of robotic networks offers a distinctive blend of computer science and control theory. The book presents a broad set of tools for understanding coordination algorithms, determining their correctness, and assessing their complexity; and it analyzes various cooperative strategies for tasks such as consensus, rendezvous, connectivity maintenance, deployment, and boundary estimation.
Home page url
Download or read it online for free here:
by Tao Zheng - InTech
Model Predictive Control refers to a class of control algorithms in which a dynamic process model is used to predict and optimize process performance. From lower request to complicated process plants, MPC has been accepted in many practical fields.
by Mario Alberto Jordan - InTech
This book covers the wide area of Discrete-Time Systems. Their contents are grouped conveniently in sections according to significant areas, namely Filtering, Fixed and Adaptive Control Systems, Stability Problems and Miscellaneous Applications.
by Ginalber Luiz de Oliveira Serra (ed.) - InTech
This book brings the state-of-art research results on advanced control from both the theoretical and practical perspectives. The fundamental and advanced research results and technical evolution of control theory are of particular interest.
by M. H. A. Davis - Tata Institute of Fundamental Research
There are actually two separate series of lectures, on controlled stochastic jump processes and nonlinear filtering respectively. They are united however, by the common philosophy of treating Markov processes by methods of stochastic calculus.