SE PhD Prospectus Defense of Nan Zhou

  • Starts: 12:00 pm on Friday, December 1, 2017
  • Ends: 2:00 pm on Friday, December 1, 2017
TITLE:Centralized and Decentralized Event-Driven Algorithms for Multi-Agent Persistent Monitoring Problems

ABSTRACT In persistent monitoring tasks, a group of cooperating mobile agents are used to monitor a dynamically changing environment that cannot be fully covered by stationary agents. The exploration process leads to the discovery of various points of interest to be perpetually monitored.

First, using optimal control, the solution can be reduced to a simpler parametric form in one-dimensional and two-dimensional mission spaces with constrained agent mobility. The behavior of agents under optimal control is described by a hybrid system which can be analyzed using Infinitesimal Perturbation Analysis (IPA) to obtain an online solution. IPA allows the modeling of virtually arbitrary stochastic effects in target uncertainty and meanwhile its event-driven nature renders the solution scalable in the number of events rather than the state space.

The second part of this work extends the previous control by developing decentralized controllers which distribute functionality to the agents. Each agent then acts upon local information and sparse communication with neighbors. Conditions are identified under which the centralized solution can be exactly recovered in a decentralized event-driven manner based on local information— except for one event requiring communication from a non-neighbor agent. As we will see, ignoring this non-local event only results in little loss of accuracy.

The last part of this work details ongoing research of parameterizing agent controls based on target thresholds in general two-dimensional settings.

COMMITTEE: Advisor: Christos G. Cassandras, SE/ECE; Sean B. Andersson, SE/ME; Alex Olshevsky, SE/ECE; Roberto Tron, SE/ME

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