Reduction of future information required for optimal control of dynamic systems: A pseudostochastic model

Avi Herbon; Eugene Khmelnitsky; Oded Maimon; Yakov Yakubov

doi:10.1109/TAC.2003.812789

Reduction of future information required for optimal control of dynamic systems: A pseudostochastic model

Avi Herbon
, Eugene Khmelnitsky
, Oded Maimon
, Yakov Yakubov

Ariel University
Tel Aviv University

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

This note develops a pseudostochastic model for optimal control of dynamic systems over a given planning horizon. The obtained results reflect the extent to which reduction of future information impacts upon the performance and optimal control of dynamic systems. The main results indicate that, when using only partial information for determining optimal control, the performance of the dynamic system is almost identical to that when using full information. When ignoring the information expected beyond the planning horizon, a significant performance loss and a possible violation of feasibility of the optimal control can occur.

Original language	English
Pages (from-to)	1025-1029
Number of pages	5
Journal	IEEE Transactions on Automatic Control
Volume	48
Issue number	6
DOIs	https://doi.org/10.1109/TAC.2003.812789
State	Published - Jun 2003
Externally published	Yes

Keywords

Information horizon
Optimal control
Stochastic processes

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10.1109/TAC.2003.812789

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abstract = "This note develops a pseudostochastic model for optimal control of dynamic systems over a given planning horizon. The obtained results reflect the extent to which reduction of future information impacts upon the performance and optimal control of dynamic systems. The main results indicate that, when using only partial information for determining optimal control, the performance of the dynamic system is almost identical to that when using full information. When ignoring the information expected beyond the planning horizon, a significant performance loss and a possible violation of feasibility of the optimal control can occur.",

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AU - Yakubov, Yakov

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AB - This note develops a pseudostochastic model for optimal control of dynamic systems over a given planning horizon. The obtained results reflect the extent to which reduction of future information impacts upon the performance and optimal control of dynamic systems. The main results indicate that, when using only partial information for determining optimal control, the performance of the dynamic system is almost identical to that when using full information. When ignoring the information expected beyond the planning horizon, a significant performance loss and a possible violation of feasibility of the optimal control can occur.

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KW - Optimal control

KW - Stochastic processes

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Reduction of future information required for optimal control of dynamic systems: A pseudostochastic model

Abstract

Keywords

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