Abstract

Active-passive dynamic consensus filters consist of a group of agents, where a subset of these agents is able to observe a quantity of interest (i.e. active agents) and the rest are subject to no observations (i.e. passive agents). Specifically, the objective of these filters is that the states of all agents are required to converge to the weighted average of the set of observations sensed by the active agents. Existing active-passive dynamic consensus filters in the classical sense assume that all agents can be modeled as having single integrator dynamics, which may not always hold in practice. Motivating from this standpoint, the contribution of this paper is to introduce a new class of active-passive dynamic consensus filters, where agents have (homogeneous) linear time-invariant dynamics. We demonstrate that for output controllable agents, the output of all active and passive agents converges to a neighborhood of the weighted average of the set of applied exogenous inputs. A numerical example is also given to illustrate the efficacy of the presented theoretical results.

Department(s)

Mechanical and Aerospace Engineering

Second Department

Electrical and Computer Engineering

Third Department

Computer Science

Comments

Air Force Office of Scientific Research, Grant None

International Standard Book Number (ISBN)

978-153867926-5

International Standard Serial Number (ISSN)

0743-1619

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.

Publication Date

01 Jul 2019

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