Brief paper: Sliding mode control for Itô stochastic systems with Markovian switching
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Stochastic algorithms for robustness of control performances
Automatica (Journal of IFAC)
Robust H2/H∞ global linearization filter design for nonlinear stochastic systems
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Central suboptimal H∞filter design for nonlinear polynomial systems
ACC'09 Proceedings of the 2009 conference on American Control Conference
Predicting numbers of performance failures in the manufacture of dynamic systems
ACC'09 Proceedings of the 2009 conference on American Control Conference
Optimal filtering over linear observations with unknown parameters
ACC'09 Proceedings of the 2009 conference on American Control Conference
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Unbiased H∞filtering for a class of stochastic systems with time-varying delay
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
On the noise-enhancing ability of stochastic hodgkin-huxley neuron systems
Neural Computation
Stochastic methods and algorithms for analysis in communication process
AMERICAN-MATH'10 Proceedings of the 2010 American conference on Applied mathematics
Filtering for discrete fuzzy stochastic systems with sensor nonlinearities
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Signal Processing
IEEE Transactions on Fuzzy Systems
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Optimal mean-square state and parameter estimation for stochastic linear systems with Poisson noises
Information Sciences: an International Journal
Journal of Control Science and Engineering - Special issue on Advances in Methods for Control over Networks
Adaptive sliding mode control for stochastic Markovian jumping systems with actuator degradation
Automatica (Journal of IFAC)
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This paper describes the robust H∞ filtering analysis and synthesis of nonlinear stochastic systems with state and exogenous disturbance-dependent noise. We assume that the state and measurement are corrupted by stochastic uncertain exogenous disturbance and that the system dynamic is modeled by Itoˆ-type stochastic differential equations. For general nonlinear stochastic systems, the H∞ filter can be obtained by solving second-order nonlinear Hamilton-Jacobi inequalities. When the worst-case disturbance is considered in the design procedure, a mixed H2/H∞ filtering problem is also solved by minimizing the total estimation error energy. It is found that for a class of special nonlinear stochastic systems, the H∞ filtering design can be given via solving several linear matrix inequalities instead of Hamilton-Jacobi inequalities. A few examples show that the proposed methods are effective.