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      Inexact Kleinman-Newton-ADI Method with Line Search to Solve Large-Scale Algebraic Riccati Equations

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      low-rank residual ADI, large-scale algebraic Riccati equation, Kleinman-Newton method, line search

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          Abstract

          This poster shows recent improvements of the inexact Kleinman-Newton method for solving algebraic Riccati equations by incorporating a line search and by systematically integrating the low-rank structure resulting from ADI methods for the approximate solution of the Lyapunov equation that needs to be solved to compute the Kleinman-Newton step. A convergence result is pointed out that tailors the convergence proof for general inexact Newton methods to the structure of Riccati equations and avoids positive semi-definiteness assumptions on the difference between certain matrices and the Lyapunov equation residual, which in general do not hold for low-rank approaches. On a test example, the improved inexact Kleinman-Newton method demonstrates its advantages.

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          Journal
          10.14293/P2199-8442.1.SOP-MATH.PSEHOS.v1

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