NDLI: Cooperative solutions in multi-person quadratic decision problems: Performance-measure statistics and cost-cumulant control paradigm

Content Provider	IEEE Xplore Digital Library
Author	Pham, K.D.
Copyright Year	2007
Description	Author affiliation: Air Force Res. Lab., Kirtland (Pham, K.D.)
Abstract	In cost-cumulant control for the class of multi-person single-objective decision problems characterized by quadratic random costs and state-feedback information structures, individual decision makers share state information with their neighbors and then autonomously determine decision strategies to achieve the desired goal of the group which is a minimization of a finite linear combination of the first k cumulants of a finite-horizon integral-quadratic performance-measure associated with a linear stochastic system. Since this problem formulation is parameterized by the number of cost cumulants, the scalar coefficients in the linear combination and the group of decision makers, it may be viewed both as a generalization of linear-quadratic Gaussian control, when the first cumulant is minimized by a single decision maker and of the problem class of linear-quadratic identical-goal stochastic games when the first cumulant is minimized by multiple decision makers. Using a more direct dynamic programming approach to the resultant initial-cost problem, it is shown that the decision laws associated with multiple persons are linear and are found as the unique solutions of the set of coupled differential matrix Riccati equations, whose solvability guarantees the existence of the closed-loop feedback decision laws for the corresponding multi-person single-objective decision problem.
Starting Page	2484
Ending Page	2490
File Size	253111
Page Count	7
File Format	PDF
ISBN	9781424414970
ISSN	01912216
DOI	10.1109/CDC.2007.4434077
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-12-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Statistics Stochastic processes Force control Laboratories Costs Riccati equations USA Councils Space vehicles Control systems Stochastic systems
Content Type	Text
Resource Type	Article

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