Distributed Consensus in Multi-vehicle Cooperative Control - Theory and Applications

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 reference for graduate courses in robotics, and linear and nonlinear control systems.

[1]  Wei Ren,et al.  Distributed attitude alignment in spacecraft formation flying , 2007 .

[2]  Vicsek,et al.  Novel type of phase transition in a system of self-driven particles. , 1995, Physical review letters.

[3]  Wei Ren,et al.  Multi-vehicle consensus with a time-varying reference state , 2007, Syst. Control. Lett..

[4]  Wei Ren Decentralization of Virtual Structures in Formation Control of Multiple Vehicle Systems via Consensus Strategies , 2008, Eur. J. Control.

[5]  Randal W. Beard,et al.  Decentralized Scheme for Spacecraft Formation Flying via the Virtual Structure Approach , 2004 .

[6]  Timothy W. McLain,et al.  Experimental validation of an autonomous control system on a mobile robot platform , 2007 .

[7]  Richard M. Murray,et al.  Information flow and cooperative control of vehicle formations , 2004, IEEE Transactions on Automatic Control.

[8]  Wei Ren,et al.  Formation Keeping and Attitude Alignment for Multiple Spacecraft Through Local Interactions , 2007 .

[9]  Jie Lin,et al.  Coordination of groups of mobile autonomous agents using nearest neighbor rules , 2003, IEEE Trans. Autom. Control..

[10]  Yongcan Cao,et al.  Simulation and Experimental Study of Consensus Algorithms for Multiple Mobile Robots with Information Feedback , 2008, Intell. Autom. Soft Comput..

[11]  Wei Ren,et al.  Distributed coordination architecture for multi-robot formation control , 2008, Robotics Auton. Syst..

[12]  Kevin L. Moore,et al.  High-Order and Model Reference Consensus Algorithms in Cooperative Control of MultiVehicle Systems , 2007 .

[13]  Wei Ren,et al.  On Constrained Nonlinear Tracking Control of a Small Fixed-wing UAV , 2007, J. Intell. Robotic Syst..

[14]  Wei Ren,et al.  Consensus strategies for cooperative control of vehicle formations , 2007 .

[15]  Randal W. Beard,et al.  Trajectory tracking for unmanned air vehicles with velocity and heading rate constraints , 2004, IEEE Transactions on Control Systems Technology.