IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v402y2021ics0096300321000679.html
   My bibliography  Save this article

A conjugate gradient method for distributed optimal control problems with nonhomogeneous Helmholtz equation

Author

Listed:
  • Zhang, Zemian
  • Chen, Xuesong

Abstract

A conjugate gradient algorithm with strong Wolfe-Powell line search for distributed optimal control problem is proposed. The optimal system has been discussed in [1]. The proposed algorithm is employed to solve the problem in infinite dimensional function space. With low complexity, it is suitable for large-scale problem. The sufficient descent condition of conjugate gradient and the existence of iterative step are proved. The algorithm also has global convergence property and linear convergence rate. At last, numerical experiments are presented to illustrate the efficiency and the convergence rate of the proposed algorithm.

Suggested Citation

  • Zhang, Zemian & Chen, Xuesong, 2021. "A conjugate gradient method for distributed optimal control problems with nonhomogeneous Helmholtz equation," Applied Mathematics and Computation, Elsevier, vol. 402(C).
  • Handle: RePEc:eee:apmaco:v:402:y:2021:i:c:s0096300321000679
    DOI: 10.1016/j.amc.2021.126019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300321000679
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2021.126019?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. William W. Hager & Hongyan Hou & Subhashree Mohapatra & Anil V. Rao & Xiang-Sheng Wang, 2019. "Convergence rate for a Radau hp collocation method applied to constrained optimal control," Computational Optimization and Applications, Springer, vol. 74(1), pages 275-314, September.
    2. Hongwei Liu & Zexian Liu, 2019. "An Efficient Barzilai–Borwein Conjugate Gradient Method for Unconstrained Optimization," Journal of Optimization Theory and Applications, Springer, vol. 180(3), pages 879-906, March.
    3. Jun Liu & Mingqing Xiao, 2016. "A leapfrog semi-smooth Newton-multigrid method for semilinear parabolic optimal control problems," Computational Optimization and Applications, Springer, vol. 63(1), pages 69-95, January.
    4. William W. Hager & Hongyan Hou & Subhashree Mohapatra & Anil V. Rao & Xiang-Sheng Wang, 2019. "Correction to: Convergence rate for a Radau hp collocation method applied to constrained optimal control," Computational Optimization and Applications, Springer, vol. 74(1), pages 315-316, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Elisha R. Pager & Anil V. Rao, 2022. "Method for solving bang-bang and singular optimal control problems using adaptive Radau collocation," Computational Optimization and Applications, Springer, vol. 81(3), pages 857-887, April.
    2. Wanchun Chen & Wenhao Du & William W. Hager & Liang Yang, 2019. "Bounds for integration matrices that arise in Gauss and Radau collocation," Computational Optimization and Applications, Springer, vol. 74(1), pages 259-273, September.
    3. Joseph D. Eide & William W. Hager & Anil V. Rao, 2021. "Modified Legendre–Gauss–Radau Collocation Method for Optimal Control Problems with Nonsmooth Solutions," Journal of Optimization Theory and Applications, Springer, vol. 191(2), pages 600-633, December.
    4. Zhu, Zhibin & Zhang, Dongdong & Wang, Shuo, 2020. "Two modified DY conjugate gradient methods for unconstrained optimization problems," Applied Mathematics and Computation, Elsevier, vol. 373(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:apmaco:v:402:y:2021:i:c:s0096300321000679. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.