id: 05564151
dt: j
an: 1162.93404
au: Zhu, Jin; Park, Junhong; Lee, Kwan-Soo; Spiryagin, Maksym
ti: Guaranteed performance robust Kalman filter for continuous-time Markovian
    jump nonlinear system with uncertain noise.
so: Math. Probl. Eng. 2008, Article ID 583947, 12 p. (2008).
py: 2008
pu: Hindawi Publishing Corporation, New York, NY
la: EN
cc: 93E11 60J75 60J25
ut: robust Kalman filtering design; Markovian jump nonlinear systems; robust
    estimation
ci: 
li: doi:10.1155/2008/583947 eudml:55490
ab: Summary: Robust Kalman filtering design for continuous-time Markovian jump
    nonlinear systems with uncertain noise was investigated. Because of
    complexity of Markovian jump systems, the statistical characteristics
    of system noise and observation noise are time-varying or unmeasurable
    instead of being stationary. In view of robust estimation, maximum
    admissible upper bound of the uncertainty to noise covariance matrix
    was given based on system state estimation performance. As long as the
    noise uncertainty is limited within this bound via noise control, the
    Kalman filter has robustness against noise uncertainty, and stability
    of dynamic systems can be ensured. It is proved by game theory that
    this design is a robust mini-max filter. A numerical example shows the
    validity of this design.
rv: