Title :
Contractions for consensus processes
Author :
Liu, J. ; Morse, A.S. ; Anderson, B.D.O. ; Yu, C.
Author_Institution :
Yale Univ., New Haven, CT, USA
Abstract :
Many distributed control algorithms of current interest can be modeled by linear recursion equations of the form x(t + 1) = M(t)x(t), t ≥ 1 where each M(t) is a real-valued “stochastic” or “doubly stochastic” matrix. Convergence of such recursions often reduces to deciding when the sequence of matrix products M(1), M(2)M(1), M(3)M(2)M(1), ... converges. Certain types of stochastic and doubly stochastic matrices have the property that any sequence of products of such matrices of the form S1, S2S1, S3S2S1, ... converges exponentially fast. We explicitly characterize the largest classes of stochastic and doubly stochastic matrices with positive diagonal entries which have these properties. The main goal of this paper is to find a “semi-norm” with respect to which matrices from these “convergability classes” are contractions. For any doubly stochastic matrix S such a semi-norm is identified and is shown to coincide with the second largest singular value of S.
Keywords :
decentralised control; distributed control; matrix algebra; stochastic processes; consensus processes; distributed control algorithms; doubly stochastic matrix; linear recursion equations; matrix products; positive diagonal entries; Convergence; Eigenvalues and eigenfunctions; Equations; Mathematical model; Stochastic processes; Symmetric matrices; Vectors;
Conference_Titel :
Decision and Control and European Control Conference (CDC-ECC), 2011 50th IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-61284-800-6
Electronic_ISBN :
0743-1546
DOI :
10.1109/CDC.2011.6160989