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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Al-Tamirni, A. Lewis, F.L. Wang, Y. |
| Copyright Year | 2007 |
| Description | Author affiliation: Univ. of Texas at Arlington, Fort Worth (Al-Tamirni, A.) |
| Abstract | In this paper, an H-infinity load-frequency controller for a power system generator will be designed without the knowledge of the system model. Uncertainty in the system model is a common problem in power systems. In this paper the strategies for discrete-time linear system quadratic zero-sum games related to the H-infinity optimal control problem are solved forward in time without knowing the system dynamical model. The idea is to solve for an action dependent value function Q(x,u,w) of the zero-sum game instead of solving for the state dependent value function V(x) which satisfies a corresponding game algebraic Riccati equation (GARE). The result is model-free approach that solves the zero-sum game forward in time; i.e. it finds an H-infinity controller without knowing the dynamical system. It is proven that the algorithm is equivalent to a model-free iterative algorithm to solve the underlying (GARE) of the linear quadratic discrete-time zero-sum game. |
| Starting Page | 118 |
| Ending Page | 125 |
| File Size | 447378 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424404407 |
| ISSN | 21589860 |
| DOI | 10.1109/ISIC.2007.4450871 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-10-01 |
| Publisher Place | Singapore |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Power system modeling Load modeling H infinity control Power system control Riccati equations Iterative algorithms Power generation Uncertainty Power system dynamics Linear systems Adaptive control Adaptive critics Approximate dynamic programming Zero-sum games Policy iterations H¿ optimal control Q-function Q-learning |
| Content Type | Text |
| Resource Type | Article |
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