A game theoretic algorithm to compute local stabilizing solutions to HJBI equations in nonlinear H control

Yantao Feng*, Brian D.O. Anderson, Michael Rotkowitz

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    49 Citations (Scopus)

    Abstract

    In this paper, an iterative algorithm to solve Hamilton-Jacobi-Bellman-Isaacs (HJBI) equations for a broad class of nonlinear control systems is proposed. By constructing two series of nonnegative functions, we replace the problem of solving an HJBI equation by the problem of solving a sequence of Hamilton-Jacobi-Bellman (HJB) equations whose solutions can be approximated recursively by existing methods. The local convergence of the algorithm and local quadratic rate of convergence of the algorithm are guaranteed and a proof is given. Numerical examples are also provided to demonstrate the effectiveness of the proposed algorithm. A game theoretical interpretation of the algorithm is given.

    Original languageEnglish
    Pages (from-to)881-888
    Number of pages8
    JournalAutomatica
    Volume45
    Issue number4
    DOIs
    Publication statusPublished - Apr 2009

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