• DocumentCode
    2793878
  • Title

    Randomized algorithms for robust control analysis and synthesis have polynomial complexity

  • Author

    Khargonekar, Pramod ; Tikku, Ashok

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
  • Volume
    3
  • fYear
    1996
  • fDate
    11-13 Dec 1996
  • Firstpage
    3470
  • Abstract
    We consider several robust control analysis and design problems. As has become well known over the last few years, most of these problems are NP hard. We show that if instead of worst-case guaranteed conclusions, one is willing to draw conclusions with a high degree of confidence, then the computational complexity decreases dramatically
  • Keywords
    computational complexity; control system analysis; control system synthesis; feedback; randomised algorithms; robust control; search problems; NP hard; polynomial complexity; randomized algorithms; robust control analysis; robust control synthesis; Algorithm design and analysis; Centralized control; Computational complexity; Control theory; Polynomials; Probability distribution; Robust control; Robust stability; Robustness; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1996., Proceedings of the 35th IEEE Conference on
  • Conference_Location
    Kobe
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-3590-2
  • Type

    conf

  • DOI
    10.1109/CDC.1996.573700
  • Filename
    573700