Adaptive dynamic programming for online solution of a zero-sum differential game
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Publication:2887631
DOI10.1007/s11768-011-0166-4zbMath1249.90308OpenAlexW2088246243MaRDI QIDQ2887631
Frank L. Lewis, Draguna Vrabie
Publication date: 1 June 2012
Published in: Journal of Control Theory and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11768-011-0166-4
Nash equilibriumzero-sum differential gameapproximate/adaptive dynamic programminggame algebraic Riccati equation
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Cites Work
- Adaptive optimal control for continuous-time linear systems based on policy iteration
- A game theoretic algorithm to compute local stabilizing solutions to HJBI equations in nonlinear \(H_\infty \) control
- An algebraic Riccati equation approach to \(H^{\infty}\) optimization
- Dynamic noncooperative game theory
- Rational matrix equations in stochastic control.
- State-space solutions to standard H/sub 2/ and H/sub infinity / control problems
- Primer on Optimal Control Theory
- L/sub 2/-gain analysis of nonlinear systems and nonlinear state-feedback H/sub infinity / control
- Kronecker products and matrix calculus in system theory
- Computing the Positive Stabilizing Solution to Algebraic Riccati Equations With an Indefinite Quadratic Term via a Recursive Method
- Policy Iterations on the Hamilton–Jacobi–Isaacs Equation for $H_{\infty}$ State Feedback Control With Input Saturation
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