Guaranteed recursive nonlinear state estimation using interval analysis

Michel Kieffer (1) , Luc Jaulin (1, 2, 3) , Eric Walter (4)

1 LISA - Laboratoire d'Ingéniérie des Systèmes Automatisés
2 STIC - Département STIC [Brest]
3 Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
4 L2S - Laboratoire des signaux et systèmes

The problem considered is state estimation in the presence of unknow state and measurement noise, each noise component being assumed to belong to some known interval. In such a bounded-error context, most available results are for linear models, and the purpose of the present paper is to deal with the nonlinear case. Based on interval analysis and the notion of set inversion, a new state estimator is presented, which evaluates a set estimate guaranteed to contain all values of the states that are consistent with the available observations, given the noise bounds and a set containing the initial value of the state. To the best of our knowledge, it is the first time that such a guaranteed estimator is made available. The precision of the set estimate can be improved, at the cost of more computation. The theorical properties of the estimator are studied, and computer implementation has received special attention. A simple illustrative example is treated.

Domaines: Sciences de l'ingénieur [physics]

Michel Kieffer, Luc Jaulin, Eric Walter. Guaranteed recursive nonlinear state estimation using interval analysis. IEEE Conference on Decision and Control, Dec 1998, Tampa (Floride), United States. pp.3966-3971. ⟨hal-00844451⟩