Distributed Consensus in Multi-vehicle Cooperative Control
Theory and Applications
Buch in deiner Nähe kaufen
Beschreibung
The coordinated use of autonomous vehicles has an abundance of potential applications from the domestic to the hazardously toxic. Frequently the communications necessary for the productive interplay of such vehicles may be subject to limitations in range, bandwidth, noise and other causes of unreliability.
Information consensus guarantees that vehicles sharing information over a network topology have a consistent view of information critical to the coordination task. Assuming only neighbor-neighbor interaction between vehicles, Distributed Consensus in Multi-vehicle Cooperative Control develops distributed consensus strategies designed to ensure that the information states of all vehicles in a network converge to a common value. This approach strengthens the team, minimizing power consumption and the deleterious effects of range and other restrictions.
The monograph is divided into six parts covering introductory, theoretical and experimental material and featuring:
• an overview of the use of consensus algorithms in cooperative control;
• consensus algorithms in single- and double-integrator dynamical systems;
• consensus algorithms for rigid-body attitude dynamics;
• rendezvous and axial alignment, formation control, deep-space formation flying, fire monitoring and surveillance.
Notation drawn from graph and matrix theory and background material on linear and nonlinear system theory are enumerated in six appendices. The authors maintain a website at which can be found a sample simulation and experimental video material associated with experiments in several chapters of this book.
Academic control systems researchers and their counterparts in government laboratories and robotics- and aerospace-related industries will find the ideas presented in Distributed Consensus in Multi-vehicle Cooperative Control of great interest. This text will also serve as a valuable support and referencefor graduate courses in robotics, and linear and nonlinear control systems.
Information consensus guarantees that robot vehicles sharing information over a network topology have a consistent view of information critical to the coordination task. Assuming only neighbor-neighbor interaction between vehicles, this monograph develops distributed consensus strategies designed to ensure that the information states of all vehicles in a network converge to a common value. This approach strengthens the team, minimizing power consumption and the effects of range and other restrictions.
The monograph covers introductory, theoretical and experimental material, featuring - an overview of the use of consensus algorithms in cooperative control; - consensus algorithms in single- and double-integrator, and rigid-body-attitude dynamics; - rendezvous and axial alignment, formation control, deep-space formation flying, fire monitoring and surveillance.
Six appendices cover material drawn from graph, matrix, linear and nonlinear systems theories.
Lays out the theoretical principles of co-ordinated control together with their experimental application Shows the reader how to deal with groups of autonomous vehicles in aerial, terrestrial and submarine environments Provides the tools to overcome impaired communication using constantly up-dated neighbor-neighbor interchange Includes supplementary material: sn.pub/extras
Autor*in
Wei Ren
Themen in »Distributed Consensus in Multi-vehicle Cooperative Control«
Monitoring Tracking algorithms autonom communication information mobile robot robot robotics systems theory unmanned aerial vehicle
Stimmen zu »Distributed Consensus in Multi-vehicle Cooperative Control«
From the reviews:
“This book gives a systematic analysis of distributed consensus problems of multivehicle cooperative control and summarizes the main recent work of the authors. The book is well written, and all of the main theoretical results are given together with rigorous mathematical proofs. This book can be a very useful reference for Ph.D. students and researchers in automatic control.” (Jinhuan Wang and Xiaoming Hu, IEEE Control Systems Magazine, Vol. 30, June, 2010)
()