A stabilization algorithm for a class of uncertain linear systems
Systems & Control Letters
Robust and optimal control
Robust H∞ -filtering design with pole placement constraint via linear matrix inequalities
Journal of Optimization Theory and Applications
H2 and H$_\infty$ Filtering Design Subject to Implementation Uncertainty
SIAM Journal on Control and Optimization
An LMI approach to discrete-time observer design with stochastic resilience
Journal of Computational and Applied Mathematics
A linear matrix inequality approach to robust H∞filtering
IEEE Transactions on Signal Processing
Induced l2 and generalized H2 filtering for systems with repeated scalar nonlinearities
IEEE Transactions on Signal Processing
Brief Non-fragile H∞ control for linear systems with multiplicative controller gain variations
Automatica (Journal of IFAC)
Technical Communique: Resilient linear filtering of uncertain systems
Automatica (Journal of IFAC)
Non-fragile H2 and H∞ filter designs for polytopic two-dimensional systems in Roesser model
Multidimensional Systems and Signal Processing
Automatica (Journal of IFAC)
International Journal of Automation and Computing
Fault-Tolerant control of a class of switched nonlinear systems with application to flight control
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part I
Insensitive reliable H∞ filtering against sensor failures
Information Sciences: an International Journal
Hi-index | 22.15 |
This paper studies the problem of non-fragile H"~ filter design for linear continuous-time systems. The filter to be designed is assumed to include additive gain variations, which result from filter implementations. A notion of structured vertex separator is proposed to approach the problem, and exploited to develop sufficient conditions for the non-fragile H"~ filter design in terms of solutions to a set of linear matrix inequalities (LMIs). The designs guarantee the asymptotic stability of the estimation errors, and the H"~ performance of the system from the exogenous signals to the estimation errors below a prescribed level. A numerical example is given to illustrate the effect of the proposed method.