An iterative algorithm to solve state-perturbed stochastic algebraic Riccati equations in LQ zero-sum games
Date
2010
Authors
Feng, Yantao
Anderson, Brian
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Volume Title
Publisher
Elsevier
Abstract
An iterative algorithm to solve a kind of state-perturbed stochastic algebraic Riccati equation (SARE) in LQ zero-sum game problems is proposed. In our algorithm, we replace the problem of solving a SARE with an indefinite quadratic term by the problem of solving a sequence of SAREs with a negative semidefinite quadratic term, which can be solved by existing methods. Under some appropriate conditions, we prove that our algorithm is globally convergent. We give a numerical example to show the effectiveness of our algorithm. Our algorithm also has a natural game theoretic interpretation.
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Keywords
Keywords: Algebraic Riccati equations; Existing method; Globally convergent; Indefinite quadratic term; Iterative algorithm; Negative semi-definite; Numerical example; Zero-sum game; Algebra; Algorithms; Game theory; Problem solving; Riccati equations; Stochastic s Iterative; SARE; Stochastic
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Source
Systems and Control Letters
Type
Journal article
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2037-12-31
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