Negotiated distributed estimation with guaranteed performance for bandwidth-limited situations

This paper proposes a guaranteed distributed estimator for large-scale, state-coupled plants. Each agent must find appropriate sets, described by zonotopes, to contain the actual state of the plant and reduce the estimation uncertainties. To do so, the agents collaborate by sending information through a network in which bandwidth restrictions need to be taken into account. An estimation algorithm is proposed, where the amount of information transmitted is negotiated through an iterative procedure that trades off communication burden and estimation performance. The negotiation process between the agents is similar to a non-cooperative game, which ends when the Nash equilibrium is reached. The algorithm can be tuned to weight estimation performance, communication costs, and discrepancies in the amount of information transmitted by neighboring agents. The estimation structure is tested by simulation on a plant consisting of a set of inverted pendulums coupled by springs.