• DocumentCode
    2338683
  • Title

    Connections between duality in control theory and convex optimization

  • Author

    Balakrishnan, V. ; Vandenberghe, L.

  • Author_Institution
    Sch. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA
  • Volume
    6
  • fYear
    1995
  • fDate
    21-23 Jun 1995
  • Firstpage
    4030
  • Abstract
    Several important problems in control theory can be reformulated as convex optimization problems. From duality theory in convex optimization, dual problems can be derived for these convex optimization problems. These dual problems can in turn be reinterpreted in control or system theoretic terms, often yielding new results or new proofs for existing results from control theory. Moreover, the most efficient algorithms for convex optimization solve the primal and dual problems simultaneously. Insight into the system-theoretic meaning of the dual problem can therefore be very helpful in developing efficient algorithms. The authors demonstrate these observations with some examples
  • Keywords
    control theory; convex programming; duality (mathematics); linear quadratic control; nonlinear programming; control theory; convex optimization; duality; Control systems; Control theory; Design optimization; Linear matrix inequalities; Linear programming; Optimization methods; Polynomials; Symmetric matrices; System analysis and design; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, Proceedings of the 1995
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    0-7803-2445-5
  • Type

    conf

  • DOI
    10.1109/ACC.1995.532689
  • Filename
    532689