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Outlier-resistant H∞ filtering for a class of networked systems under Round-Robin protocol
- Source :
- Neurocomputing. 403:133-142
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
Abstract
- In this paper, the H∞ filtering problem is addressed for a class of nonlinear stochastic discrete-time systems subject to Round-Robin protocol, measurement outliers, randomly occurring parameter uncertainties and randomly occurring nonlinearities. First of all, the considered system is influenced by the parameter uncertainties, nonlinear dynamics and external disturbances. Next, mutually independent Bernoulli-distributed white sequences are employed to describe the phenomena of randomly occurring parameter uncertainties and nonlinearities, respectively. Besides, the Round-Robin protocol is introduced to prevent the occurrence of data collisions during the signal transmission. Moreover, a filter with adaptive saturation is constructed to weaken the impact of the measurement outliers. Through constructing a suitable Lyapunov function, sufficient conditions are established to ensure that the error system dynamics is exponentially mean-square stable and satisfies the H∞ performance. Subsequently, the filter gains are designed by solving a set of linear matrix inequalities. Finally, a simulation example is given to show the effectiveness of the filtering scheme proposed in this paper.
- Subjects :
- Lyapunov function
0209 industrial biotechnology
Computer science
Cognitive Neuroscience
02 engineering and technology
Filter (signal processing)
Computer Science Applications
Set (abstract data type)
Nonlinear system
symbols.namesake
020901 industrial engineering & automation
Artificial Intelligence
Control theory
Outlier
0202 electrical engineering, electronic engineering, information engineering
symbols
Filtering problem
020201 artificial intelligence & image processing
Protocol (object-oriented programming)
Subjects
Details
- ISSN :
- 09252312
- Volume :
- 403
- Database :
- OpenAIRE
- Journal :
- Neurocomputing
- Accession number :
- edsair.doi...........d4472e9476d0fd1479439f17210d5971