Control and Estimation Algorithms for Multiple-Agent Systems
Stankovic, Milos
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https://hdl.handle.net/2142/87096
Description
Title
Control and Estimation Algorithms for Multiple-Agent Systems
Author(s)
Stankovic, Milos
Issue Date
2009
Doctoral Committee Chair(s)
Dusan Stipanovic
Sreenivas, Ramavarapu S.
Department of Study
Systems and Entrepreneurial Engineering
Discipline
Systems and Entrepreneurial Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Mechanical
Language
eng
Abstract
Motivated by the applications to the optimal mobile sensor positioning within mobile sensor networks, the perturbation-based extremum seeking algorithm has been modified and extended. It has been assumed that the integrator gain and the perturbation amplitude are time varying (decreasing in time with a proper rate) and that the output is corrupted with measurement noise. The proposed basic, one dimensional, algorithm has been extended to two dimensional, hybrid schemes and directly applied to the planar optimal mobile sensor positioning, where the vehicles can be modeled as velocity actuated point masses, force actuated point masses, or nonholonomic unicycles. The convergence of all the proposed algorithms, with probability one and in the mean square sense, has been proved. Also, the problem of target assignment in multi-agent systems using multi-variable extremum seeking algorithm has been addressed. An algorithm which effectively solves the problem has been proposed, based on the local extremum seeking of the specially designed global utility functions which capture the dependance among different, possibly conflicting objectives of the agents. It has been demonstrated how the utility function parameters and agents' initial conditions impact the trajectories and destinations of the agents. All the proposed extremum seeking based algorithms have been illustrated with several simulations.
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