• DocumentCode
    240303
  • Title

    Closed-loop development for dissipativity constraint

  • Author

    Tri Tran ; Ling, K.-V. ; Maciejowski, Jan M.

  • Author_Institution
    Nanyang Technol. Univ., Singapore, Singapore
  • fYear
    2014
  • fDate
    2-5 Dec. 2014
  • Firstpage
    24
  • Lastpage
    29
  • Abstract
    The quadratic dissipativity constraint (QDC), a generalization of the asymptotically positive realness constraint (APRC), has previously been introduced and developed into an enforced stability constraint for the model predictive control schemes. This paper presents the novel development for a static constrained-state feedback control of interconnected systems, in which the decentralized QDC is employed for assuring the closed-loop stability of the global large-scale system. In this work, the input-and-power-to-state stability (IpSS), an extension of the input-to-state stability (ISS), is achieved. Under the realm of IpSS, the system stability does not rely on the monotonically reducing Lyapunov function. As a result, the proposed method provides a less conservative decentralized control law compared to those synthesized with the traditional Lyapunov stability condition. Simulation studies with small-signal linear models of three typical power systems are presented to demonstrate the effectiveness of the QDC, especially for systems having state constraints.
  • Keywords
    Lyapunov methods; closed loop systems; decentralised control; interconnected systems; linear systems; predictive control; stability; state feedback; APRC; IpSS; Lyapunov stability condition; asymptotically positive realness constraint; closed-loop development; closed-loop stability; decentralized QDC; input-and-power-to-state stability; interconnected system; model predictive control scheme; monotonically reducing Lyapunov function; quadratic dissipativity constraint; small-signal linear model; stability constraint; state constraint; static constrained-state feedback control; Asymptotic stability; Load modeling; Numerical models; Power system stability; Stability analysis; State feedback; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control, Automation and Information Sciences (ICCAIS), 2014 International Conference on
  • Conference_Location
    Gwangju
  • Type

    conf

  • DOI
    10.1109/ICCAIS.2014.7020562
  • Filename
    7020562