Sum of Squares Polynomial Approximate Dynamic Programming for the Ergodic Problem
The purpose of this note is to extend the approximate dynamic programming (ADP) method to the infinite time stochastic optimal control (ergodic) problem. It is also shown that a modification of the basic algorithm solves the output feedback problem. The ADP solution of the ergodic problem differs in...
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| Veröffentlicht in: | IEEE transactions on automatic control Jg. 70; H. 9; S. 6253 - 6259 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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New York
IEEE
01.09.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| Abstract | The purpose of this note is to extend the approximate dynamic programming (ADP) method to the infinite time stochastic optimal control (ergodic) problem. It is also shown that a modification of the basic algorithm solves the output feedback problem. The ADP solution of the ergodic problem differs in significant ways from its deterministic counterpart. |
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| AbstractList | The purpose of this note is to extend the approximate dynamic programming (ADP) method to the infinite time stochastic optimal control (ergodic) problem. It is also shown that a modification of the basic algorithm solves the output feedback problem. The ADP solution of the ergodic problem differs in significant ways from its deterministic counterpart. |
| Author | Hexner, Gyorgy |
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| SubjectTerms | Approximate dynamic programming Approximation algorithms Closed loop systems Dynamic programming ergodic systems Iterative methods Mathematical models Minimization Optimal control Output feedback Polynomials Stability criteria stochastic control |
| Title | Sum of Squares Polynomial Approximate Dynamic Programming for the Ergodic Problem |
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