Asynchronous State Estimation for Discrete-Time Switched Complex Networks With Communication Constraints

This paper is concerned with the asynchronous state estimation for a class of discrete-time switched complex networks with communication constraints. An asynchronous estimator is designed to overcome the difficulty that each node cannot access to the topology/coupling information. Also, the event-ba...

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Veröffentlicht in:IEEE transaction on neural networks and learning systems Jg. 29; H. 5; S. 1732 - 1746
Hauptverfasser: Zhang, Dan, Wang, Qing-Guo, Srinivasan, Dipti, Li, Hongyi, Yu, Li
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States IEEE 01.05.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Asynchronous switching
Communication
Communications systems
Complex networks
Convexity
Error detection
event-based communication
Optimization
random packet dropouts
signal quantization
State estimation
Stochasticity
switched complex networks
Switches
Switching theory
Symmetric matrices
Synchronization
System theory
Systems analysis
Systems theory
Topology
ISSN:2162-237X, 2162-2388, 2162-2388
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Zusammenfassung:This paper is concerned with the asynchronous state estimation for a class of discrete-time switched complex networks with communication constraints. An asynchronous estimator is designed to overcome the difficulty that each node cannot access to the topology/coupling information. Also, the event-based communication, signal quantization, and the random packet dropout problems are studied due to the limited communication resource. With the help of switched system theory and by resorting to some stochastic system analysis method, a sufficient condition is proposed to guarantee the exponential stability of estimation error system in the mean-square sense and a prescribed <inline-formula> <tex-math notation="LaTeX">H_{\infty } </tex-math></inline-formula> performance level is also ensured. The characterization of the desired estimator gains is derived in terms of the solution to a convex optimization problem. Finally, the effectiveness of the proposed design approach is demonstrated by a simulation example.
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ISSN:2162-237X
2162-2388
2162-2388
DOI:10.1109/TNNLS.2017.2678681