Abstract
A set of stochastic matrices P is a consensus set if for every sequence of matrices P(1), P(2), . . . whose elements belong to P and every initial state x(0), the sequence of states defined by x(t) = P(t)P(t-1) . . . P(1)x(0) converges to a vector whose entries are all identical. In this paper, we introduce an "avoiding set condition" for compact sets of matrices and prove in our main theorem that this explicit combinatorial condition is both necessary and sufficient for consensus. We show that several of the conditions for consensus proposed in the literature can be directly derived from the avoiding set condition. The avoiding set condition is easy to check with an elementary algorithm, and so our result also establishes that consensus is algorithmically decidable. Direct verification of the avoiding set condition may require more than a polynomial time number of operations. This is, however, likely to be the case for any consensus checking algorithm since we also prove in this paper that unless P = NP, consensus cannot be decided in polynomial time.
Original language | English (US) |
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Pages (from-to) | 2707-2726 |
Number of pages | 20 |
Journal | SIAM Journal on Control and Optimization |
Volume | 52 |
Issue number | 5 |
DOIs | |
State | Published - 2014 |
Externally published | Yes |
Keywords
- Computational complexity
- Consensus
- Switched systems
ASJC Scopus subject areas
- Control and Optimization
- Applied Mathematics