• DocumentCode
    116196
  • Title

    Further results on the maximal contractively invariant ellipsoid of discrete-time linear systems with multiple inputs subject to actuator saturation

  • Author

    Yuanlong Li ; Zongli Lin

  • Author_Institution
    Dept. of Autom., Shanghai Jiao Tong Univ., Shanghai, China
  • fYear
    2014
  • fDate
    15-17 Dec. 2014
  • Firstpage
    6311
  • Lastpage
    6316
  • Abstract
    Contractively invariant ellipsoids have been extensively used as estimates of the domain of attraction of a linear system under a saturated linear feedback. For a discrete-time linear system with a single input subject to actuator saturation, based on a convex hull representation of the saturated linear feedback, a necessary and sufficient condition for an ellipsoid to be contractively invariant was previously established. Based on this condition, the determination of the maximal contractively invariant ellipsoid can be formulated and solved as an LMI problem. In this paper, we develop a criterion to determine if a contractively invariant ellipsoid is the maximal one for discrete-time saturated linear systems with multiple inputs. This criterion is based on the solution of an LMI problem, which involves a generalized convex hull representation of saturated linear feedbacks, and includes the existing result for discrete-time saturated linear systems with a single input as a special case. Simulation results demonstrate the effectiveness of our results.
  • Keywords
    discrete time systems; feedback; linear matrix inequalities; linear systems; LMI problem; actuator saturation; attraction domain; convex hull representation; discrete-time saturated linear system; linear matrix inequality; maximal contractively invariant ellipsoid; necessary condition; saturated linear feedback; sufficient condition; Actuators; Eigenvalues and eigenfunctions; Ellipsoids; Linear matrix inequalities; Linear systems; Lyapunov methods; Optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-1-4799-7746-8
  • Type

    conf

  • DOI
    10.1109/CDC.2014.7040378
  • Filename
    7040378