• DocumentCode
    1255236
  • Title

    Set-Membership Filtering with State Constraints

  • Author

    Yang, Fuwen ; Li, Yongmin

  • Author_Institution
    Dept. of Inf. Syst. & Comput., Brunel Univ., Uxbridge, UK
  • Volume
    45
  • Issue
    4
  • fYear
    2009
  • Firstpage
    1619
  • Lastpage
    1629
  • Abstract
    In this paper, the problem of set-membership filtering is considered for discrete-time systems with equality and inequality constraints between their state variables. We formulate the problem of set-membership filtering as finding the set of estimates that belong to an ellipsoid. A centre and a shape matrix of the ellipsoid are used to describe the set of estimates and the solution to the set of estimates is obtained in terms of matrix inequality. Unknown but bounded process and measurement noises are handled under the inequality constraints by using S-procedure. We apply Finsler´s lemma to project the set of estimates onto the constrained surface. A recursive algorithm is developed for computing the ellipsoid that guarantees to contain the true state under the state constraints, which is easily implemented by semi-definite programming via interior-point approach. A vehicle tracking example is provided to demonstrate the effectiveness of the proposed set-membership filtering with state equality constraints.
  • Keywords
    discrete time systems; filtering theory; matrix algebra; Finsler lemma; S-procedure; discrete-time systems; equality-inequality constraints; matrix inequality; semidefinite programming; set-membership filtering; shape matrix; state constraints; state equality constraints; vehicle tracking example; Ellipsoids; Filtering; Kalman filters; Linear matrix inequalities; Noise measurement; Noise shaping; Road vehicles; Shape; State estimation; Uncertain systems;
  • fLanguage
    English
  • Journal_Title
    Aerospace and Electronic Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9251
  • Type

    jour

  • DOI
    10.1109/TAES.2009.5310323
  • Filename
    5310323