Cooperative Control of Distributed Multi-Agent Systems

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Edition: 1st
Format: Hardcover
Pub. Date: 2008-01-22
Publisher(s): Wiley-Interscience
List Price: $262.34

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Summary

This book presents the results of a  "MURI" (Multidisciplinary University Research Initiative) projects on the topic.  The material is organized under four broad themes, or dimensions of cooperative control. These are: _ Distributed control & computation: The defining characteristic of cooperative control, namely, the distributed nature of decision making among interacting components. Adversarial interactions: A driving motivation for this project is autonomous vehicle systems operating in a possibly hostile environment. The presence of other hostile vehicles that are capable of strategic planning brings into play notions from non-cooperative game theory.   Uncertain evolution: The operating environment introduces significant uncertainty in the operation of autonomous vehicle systems and Complexity management: Cooperative control formulations, if taken at face value, often result in computationally prohibitive solutions.

Author Biography

Jeff Shamma's research interest is feedback control and systems theory. He received a Ph.D. in Systems Science and Engineering in 1988 from the Massachusetts Institute of Technology, Department of Mechanical Engineering. His previous faculty positions have included the University of Minnesota, Minneapolis, and the University of Texas, Austin. Since 1999, he has been with UCLA, where he is currently a Professor of Mechanical and Aerospace Engineering. He served as the MAE Department Vice Chair for Graduate Affairs from 2000-2002.  Jeff Shamma is also the recipient of the NSF Young Investigator Award (1992), a recipient of the American Automatic Control Council Donald P. Eckman Award (1996), a past Plenary Speaker at the American Control Conference (1998), and a Fellow of the IEEE (2006).  He has served on the editorial boards of the IEEE Transactions on Automatic Control and Systems & Control Letters.

Table of Contents

Introduction
Dimensions of cooperative control
Why cooperative control?
Dimensions of cooperative control
Future directions
Acknowledgements
References
Distributed Control and Computation
Design of behavior of swarms: From flocking to data fusion using microfilter networks
Introduction
Consensus problems
Flocking behavior for distributed coverage
Microfilter networks for cooperative data fusion
Acknowledgements
References
Connectivity and convergence of formations
Introduction
Problem formulation
Algebraic graph theory
Stability of vehicle formations in the case of time-invariant communication
Stability of vehicle formations in the case of time-variant communication
Stabilizing feedback for the time-variant communication case
Graph connectivity and stability of vehicle formations
Conclusion
Acknowledgements
References
Distributed receding horizon control: stability via move suppression
Introduction
System description and objective
Distributed receding horizon control
Feasibility and stability analysis
Conclusion
Acknowledgements
References
Distributed predictive control: synthesis, stability and feasibility
Introduction
Problem formulation
Distributed MPC scheme
DMPC stability analysis
Distributed design for identical unconstrained LTI subsystems
Ensuring feasibility
Conclusion
References
Task assignment for mobile agents
Introduction
Background
Problem statement
Assignment algorithm and results
Simulations
Conclusions
Acknowledgements
References
On the value of information in dynamic multiple-vehicle routing problems
Introduction
Problem formulation
Control policy description
Performance analysis in light load
A performance analysis for sTP, mTP/FG and mTP policies
Some numerical results
Conclusions
References
Optimal agent cooperation with local information
Introduction
Notation and problem formulation
Mathematical problem formulation
Algorithm overview and LP decomposition
Fixed point computation
Discussion and examples
Conclusion
Acknowledgements
References
Multiagent cooperation through egocentric modeling
Introduction
Centralized and decentralized optimization
Evolutionary cooperation
Analysis of convergence
Conclusion
Acknowledgements
References
Adversarial Interactions
Multi-vehicle cooperative control using mixed integer linear programming
Introduction
Vehicle dynamics
Obstacle avoidance
RoboFlag problems
Average case complexity
Discussion
Appendix: Converting logic into inequalities
Acknowledgements
References
LP-based multi-vehicle path planning with adversaries
Table of Contents provided by Publisher. All Rights Reserved.

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