A game theoretic algorithm to solve riccati and hamilton-jacobi-bellman-isaacs (HJBI) equations in H control

Brian D.O. Anderson, Yantao Feng, Weitian Chen

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    2 Citations (Scopus)

    Abstract

    In this chapter, we propose a new algorithm to solve Riccati equations and certain Hamilton-Jacobi-Bellman-Isaacs (HJBI) equations arising in H control. The need for the algorithm is motivated by the existence of H problems for which standard Riccati solvers break down, but which can be handled by the algorithm. By using our algorithm, we replace the problem of solving H Riccati equations or HJBI equations by the problem of solving a sequence of H2 Riccati equations or Hamilton-Jacobi-Bellman (HJB) equations. The algorithms have some advantages such as a simple initialization, local quadratic rate of convergence, and a natural game theoretic interpretation. Some numerical examples are given to demonstrate advantages of our algorithm.

    Original languageEnglish
    Title of host publicationSpringer Optimization and Its Applications
    PublisherSpringer International Publishing Switzerland
    Pages277-308
    Number of pages32
    DOIs
    Publication statusPublished - 2010

    Publication series

    NameSpringer Optimization and Its Applications
    Volume39
    ISSN (Print)1931-6828
    ISSN (Electronic)1931-6836

    Fingerprint

    Dive into the research topics of 'A game theoretic algorithm to solve riccati and hamilton-jacobi-bellman-isaacs (HJBI) equations in H control'. Together they form a unique fingerprint.

    Cite this