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Non-fragile H∞ state estimation for nonlinear networked system with probabilistic diverging disturbance and multiple missing measurements
- Source :
- Neurocomputing. 230:270-278
- Publication Year :
- 2017
- Publisher :
- Elsevier BV, 2017.
-
Abstract
- This paper is concerned with the non-fragile H ∞ state estimation problem for a class of discrete-time networked system with probabilistic diverging disturbance and multiple missing measurements. The measurement missing phenomenon is assumed to occur randomly and the missing probability for each sensor is governed by an individual random variable satisfying a certain probabilistic distribution over the interval 0 , 1 . The aim of this paper is to estimate the networked system by designing a non-fragile H ∞ estimator such that the augmented estimation error system is asymptotically mean square stable with a prescribed H ∞ disturbance attention level γ. By using the Lyapunov method and stochastic analysis, we derive a sufficient condition for the existence of the desired estimator. By solving the linear matrix inequalities (LMIs), the estimator gain matrix is given. Two numerical examples are employed to demonstrate the effectiveness and applicability of the proposed design technique.
- Subjects :
- Lyapunov function
0209 industrial biotechnology
Stochastic process
Cognitive Neuroscience
Probabilistic logic
Estimator
02 engineering and technology
Interval (mathematics)
Computer Science Applications
Matrix (mathematics)
Nonlinear system
symbols.namesake
020901 industrial engineering & automation
Artificial Intelligence
Control theory
0202 electrical engineering, electronic engineering, information engineering
symbols
020201 artificial intelligence & image processing
Random variable
Mathematics
Subjects
Details
- ISSN :
- 09252312
- Volume :
- 230
- Database :
- OpenAIRE
- Journal :
- Neurocomputing
- Accession number :
- edsair.doi...........4617788accd0bc429142a92efdc3e46d