Seminar Series

As part of the work, and to facilitate communication among team members, the project has instituted a seminar series where team members and/or invited speakers share their ideas. Graduate students are particularly invited to attend.

SEMINAR NOTES:

• First Seminar

  • Multiple-Model Approach to Hybrid Estimation by X. Rong Li Department of Electrical Engineering University of New Orleans New Orleans, LA 70148, USA xli@uno.edu, Tel: 504-280-7416, Fax: 504-280-3950 Abstract Hybrid estimation refers to estimation of a hybrid random process with jump as well as diffusion components, such as state estimation for a hybrid system, which includes both continuous- and discrete-valued state variables.  It unifies conventional estimation and decision, and provides a powerful framework for many inference problems (e.g., detection, estimation, recognition, and identification) involving both structural and parametric uncertainties/changes, among others.   An introduction to hybrid estimation is given. One of the most natural and popular approach to hybrid estimation is the so-called multiple-model method.  It uses more than one model at every time to represent or cover possibilities of the unknown structures; the overall estimate is a combination of single-model-based estimates; and the probability/likelihood of a model provides a quantitative measure of the unknown true structure. An overview of multiple-model estimation approach is presented.  Its basic ideas are explained.  Its three generations (autonomous, interacting, and variable structure) are described.  An application example for detection and identification of aircraft sensor and actuator faults are given.  Historical milestones, recent advances, and open problems of the multiple-model approach are addressed. Notes from first lecture Close