Doctoral Dissertations

Keywords and Phrases

Active Passive Consensus; Distributed Control; Dynamic Consensus Filters; Linear Time Invariant Agents; Multiagent Control; Multiagent Systems


”This dissertation presents a new method for distributively sensing dynamic environments utilizing integral action based system theoretic distributed information fusion methods. Specifically, the main contribution is a new class of dynamic consensus filters, termed active-passive dynamic consensus filters, in which agents are considered to be active, if they are able to sense an exogenous quantity of interest and are considered to be passive, otherwise, where the objective is to drive the states of all agents to the convex hull spanned by the exogenous inputs sensed by active agents. Additionally, we generalize these results to allow agents to locally set their value-of-information, characterizing an agents ability to sense a local quantity of interest, which may change with respect to time.

The presented active-passive dynamic consensus filters utilize equations of motion in order to diffuse information across the network, requiring continuous information exchange and requiring agents to exchange their measurement and integral action states. Additionally, agents are assumed to be modeled as having single integrator dynamics. Motivated from this standpoint, we utilize the ideas and results from event-triggering control theory to develop a network of agents which only share their measurement state information as required based on errors exceeding a user-defined threshold. We also develop a static output-feedback controller which drives the outputs of a network of agents with general linear time-invariant dynamics to the average of a set of applied exogenous inputs. Finally, we also present a system state emulator based adaptive controller to guarantee that agents will reach a consensus even in the presence of input disturbances.

For each proposed active-passive dynamic consensus filter, a rigorous analysis of the closed-loop system dynamics is performed to demonstrate stability. Finally, numerical examples and experimental studies are included to demonstrate the efficacy of the proposed information fusion filters”--Abstract, page iv.


Balakrishnan, S. N.

Committee Member(s)

Yucelen, Tansel
Sarangapani, Jagannathan, 1965-
Casbeer, David
Landers, Robert G.
Krishnamurthy, K.


Mechanical and Aerospace Engineering

Degree Name

Ph. D. in Mechanical Engineering


Missouri University of Science and Technology

Publication Date

Spring 2019

Journal article titles appearing in thesis/dissertation

  • Distributed control of active-passive networked multiagent systems
  • An active-passive networked multiagent systems approach to environment surveillance
  • Application of an active-passive dynamic consensus filters approach to the multiagent tracking problem for situational awareness in unknown environments
  • Exploitation of heterogeneity in distributed sensing: An active-passive networked multiagent systems approach
  • Active-passive dynamic consensus filters with reduced information exchange and time-varying agent roles
  • Resilient control of linear time-invariant networked multiagent systems
  • Active-passive dynamic consensus filters for linear time-invariant multiagent systems


xv, 178 pages

Note about bibliography

Includes bibliographic references.


© 2019 John Daniel Peterson, All rights reserved.

Document Type

Dissertation - Open Access

File Type




Thesis Number

T 12044

Electronic OCLC #