Algorithms for Leader Selection in Stochastically Forced Consensus Networks

• Published in: IEEE transactions on automatic control Vol. 59; no. 7; pp. 1789 - 1802
• Main Authors: Fu Lin, Fardad, Makan, Jovanovic, Mihailo R.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Automatic control; Boolean algebra; Convex functions; Deviation; Greedy algorithms; Heuristic; Laplace equations; Linear programming; Networks; Position (location); Probability theory; Randomness; Trajectory; Upper bound; Vectors; semidefinite programming (SDP); leader selection; sensor selection; convex optimization; consensus networks; greedy algorithm; variance amplification; Alternating direction method of multipliers (ADMMs); performance bounds; convex relaxations

We are interested in assigning a pre-specified number of nodes as leaders in order to minimize the mean-square deviation from consensus in stochastically forced networks. This problem arises in several applications including control of vehicular formations and localization in sensor networks. For ne...