State-dependent Riccati equation control with predicted trajectory

A. Dutka, M.J. Grimble

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

4 Citations (Scopus)

Abstract

A modified State-Dependent Riccati Equation method is used which takes into account future variations in the system model dynamics. The system in the state dependent coefficient form, together with the prediction of the future trajectory, may be considered to be approximated by known time-varying system. For such a system the optimal control solution may be obtained for a discrete time system by solving the Riccati Difference Equation. The minimisation of the cost function for a predicted time-varying system is achieved by considering the prediction horizon as a combination of infinite and finite horizon parts. The infinite part is minimised by solving the Algebraic Riccati Equation and the finite part by the Riccati Difference Equation. The number of future prediction steps depends upon the problem and is a fixed variable chosen during the controller design. A comparison of results is provided with other design methods, which indicates that there is considerable potential for the technique.
LanguageEnglish
Title of host publicationProceedings of the 2004 American Control Conference
Place of PublicationNew York
PublisherIEEE
Pages1563-1568
Number of pages6
ISBN (Print)0780383354
Publication statusPublished - Jun 2004
EventAmerican Control Conference 2004 - Boston, United States
Duration: 30 Jun 20042 Jul 2004

Publication series

NameProceedings of the American Control Conference
PublisherIEEE
ISSN (Print)0743-1619

Conference

ConferenceAmerican Control Conference 2004
CountryUnited States
CityBoston
Period30/06/042/07/04

Fingerprint

Riccati equations
Time varying systems
Trajectories
Difference equations
Cost functions
Dynamic models
Controllers

Keywords

  • state-dependent
  • riccati equation control
  • predicted trajectory
  • riccati equations
  • time-varying systems
  • optimal control
  • minimisation
  • infinite horizon
  • discrete time systems
  • difference equations
  • control system synthesis

Cite this

Dutka, A., & Grimble, M. J. (2004). State-dependent Riccati equation control with predicted trajectory. In Proceedings of the 2004 American Control Conference (pp. 1563-1568). (Proceedings of the American Control Conference). New York: IEEE.
Dutka, A. ; Grimble, M.J. / State-dependent Riccati equation control with predicted trajectory. Proceedings of the 2004 American Control Conference. New York : IEEE, 2004. pp. 1563-1568 (Proceedings of the American Control Conference).
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abstract = "A modified State-Dependent Riccati Equation method is used which takes into account future variations in the system model dynamics. The system in the state dependent coefficient form, together with the prediction of the future trajectory, may be considered to be approximated by known time-varying system. For such a system the optimal control solution may be obtained for a discrete time system by solving the Riccati Difference Equation. The minimisation of the cost function for a predicted time-varying system is achieved by considering the prediction horizon as a combination of infinite and finite horizon parts. The infinite part is minimised by solving the Algebraic Riccati Equation and the finite part by the Riccati Difference Equation. The number of future prediction steps depends upon the problem and is a fixed variable chosen during the controller design. A comparison of results is provided with other design methods, which indicates that there is considerable potential for the technique.",
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Dutka, A & Grimble, MJ 2004, State-dependent Riccati equation control with predicted trajectory. in Proceedings of the 2004 American Control Conference. Proceedings of the American Control Conference, IEEE, New York, pp. 1563-1568, American Control Conference 2004 , Boston, United States, 30/06/04.

State-dependent Riccati equation control with predicted trajectory. / Dutka, A.; Grimble, M.J.

Proceedings of the 2004 American Control Conference. New York : IEEE, 2004. p. 1563-1568 (Proceedings of the American Control Conference).

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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N1 - © 2004 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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N2 - A modified State-Dependent Riccati Equation method is used which takes into account future variations in the system model dynamics. The system in the state dependent coefficient form, together with the prediction of the future trajectory, may be considered to be approximated by known time-varying system. For such a system the optimal control solution may be obtained for a discrete time system by solving the Riccati Difference Equation. The minimisation of the cost function for a predicted time-varying system is achieved by considering the prediction horizon as a combination of infinite and finite horizon parts. The infinite part is minimised by solving the Algebraic Riccati Equation and the finite part by the Riccati Difference Equation. The number of future prediction steps depends upon the problem and is a fixed variable chosen during the controller design. A comparison of results is provided with other design methods, which indicates that there is considerable potential for the technique.

AB - A modified State-Dependent Riccati Equation method is used which takes into account future variations in the system model dynamics. The system in the state dependent coefficient form, together with the prediction of the future trajectory, may be considered to be approximated by known time-varying system. For such a system the optimal control solution may be obtained for a discrete time system by solving the Riccati Difference Equation. The minimisation of the cost function for a predicted time-varying system is achieved by considering the prediction horizon as a combination of infinite and finite horizon parts. The infinite part is minimised by solving the Algebraic Riccati Equation and the finite part by the Riccati Difference Equation. The number of future prediction steps depends upon the problem and is a fixed variable chosen during the controller design. A comparison of results is provided with other design methods, which indicates that there is considerable potential for the technique.

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Dutka A, Grimble MJ. State-dependent Riccati equation control with predicted trajectory. In Proceedings of the 2004 American Control Conference. New York: IEEE. 2004. p. 1563-1568. (Proceedings of the American Control Conference).