Event-triggered reliable dissipative filtering for nonlinear networked control systems
| Autor: | Pengbiao Wang, Yingnan Pan, Guang-Hong Yang |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Computer science Cognitive Neuroscience 02 engineering and technology Filter (signal processing) Fuzzy logic Computer Science Applications Nonlinear system 020901 industrial engineering & automation Exponential stability Artificial Intelligence Control theory Asynchronous communication Control system 0202 electrical engineering electronic engineering information engineering Dissipative system Filtering problem 020201 artificial intelligence & image processing |
| Zdroj: | Neurocomputing. 360:120-130 |
| ISSN: | 0925-2312 |
| Popis: | This paper investigates the event-triggered reliable dissipative filtering problem for nonlinear networked control systems (NCSs) described by interval type-2 T-S fuzzy models. First, a novel adaptive event-triggered scheme is proposed to save the limited network resources. Then, a new event-triggered reliable dissipative filter is designed subject to mismatched membership functions and asynchronous constraints. Furthermore, sufficient conditions for ensuring asymptotic stability and strict dissipativity of the filtering error system are derived by utilizing slack matrices and the information of the membership functions. Compared with the existing event-triggered schemes, it is shown that the proposed one can more effectively reduce the utilization of network resources while ensuring the better estimation performance. Finally, a simulation example is given to illustrate the advantages of the proposed method. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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