A game theory approach to robust discrete-timeH∞-estimation
IEEE Transactions on Signal Processing
Minimax robust deconvolution filters under stochastic parametricand noise uncertainties
IEEE Transactions on Signal Processing
Brief paper: A set-membership state estimation algorithm based on DC programming
Automatica (Journal of IFAC)
Improved state estimation of stochastic systems
MATH'07 Proceedings of the 12th WSEAS International Conference on Applied Mathematics
Improved estimation of state of stochastic systems via invariant embedding technique
WSEAS Transactions on Mathematics
Brief paper: Set-membership filtering for systems with sensor saturation
Automatica (Journal of IFAC)
A discrete-time robust extended Kalman filter
ACC'09 Proceedings of the 2009 conference on American Control Conference
Set-membership fuzzy filtering for nonlinear discrete-time systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A model validation approach to texture recognition and inpainting
Pattern Recognition
Robust H∞ finite-horizon filtering with randomly occurred nonlinearities and quantization effects
Automatica (Journal of IFAC)
Brief paper: H∞ filtering with randomly occurring sensor saturations and missing measurements
Automatica (Journal of IFAC)
Brief Guaranteed state estimation by zonotopes
Automatica (Journal of IFAC)
Hi-index | 22.15 |
The paper presents a new approach to robust state estimation for a class of uncertain discrete-time systems with a deterministic description of noise and uncertainty. The main result is a recursive scheme for constructing an ellipsoidal state estimation set of all states consistent with the measured output and the given noise and uncertainty description. The paper also includes a result on model validation whereby it can be determined if the assumed model is consistent with measured data.