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A Game Theoretic Algorithm to Solve Riccati and Hamilton—Jacobi—Bellman—Isaacs (HJBI) Equations in H Control

  • Brian D. O. AndersonEmail author
  • Yantao FengEmail author
  • Weitian ChenEmail author
Chapter
Part of the Springer Optimization and Its Applications book series (SOIA, volume 39)

Summary

In this chapter, we propose a new algorithm to solve Riccati equations and certain Hamilton—Jacobi—Bellman—Isaacs (HJBI) equations arising in \(H_{\infty}\) control. The need for the algorithm is motivated by the existence of \(H_{\infty}\) 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 \(H_{\infty}\) Riccati equations or HJBI equations by the problem of solving a sequence of H 2 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.

Keywords

Riccati HJBI iterative game theoretic convergence 

Notes

Acknowledgment

This work has been supported in part by Australian Research Council Discovery Project Grant DP0664427.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Research School of Information Sciences and Engineeringthe Australian National UniversityCanberraAustralia
  2. 2.National ICT AustraliaCanberraAustralia

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