DocumentCode :
130129
Title :
Distributed fault estimation of networked systems using quantized measurements
Author :
Rongyao Ling ; Xiaobo Dong ; Dan Zhang ; Li Yu
Author_Institution :
Coll. of Inf. Eng., Zhejiang Univ. of Technol., Hangzhou, China
fYear :
2014
fDate :
28-30 July 2014
Firstpage :
949
Lastpage :
954
Abstract :
This paper is concerned with the problem of distributed fault estimation for networked systems using quantized measurements. In the proposed distributed scheme each estimator provides a fault estimate by adopting both its local measurement and information from neighbors, which are quantized before transmission due to the limited bandwidth resource. A sector bound approach is firstly introduced to handle the quantization error. Then the dynamics of estimation errors are modeled as a system with uncertainties. Based on the Lyapunov stability theory, a sufficient condition is derived such that the estimation error system is asymptotically stable and achieves a prescribed H noise attenuation performance. A convex optimization problem is formulated for designing the desired distributed estimators. Finally, an illustrative example is presented to demonstrate the effectiveness of the proposed design method.
Keywords :
H control; Lyapunov methods; asymptotic stability; control system synthesis; distributed control; fault tolerant control; networked control systems; quantisation (signal); H noise attenuation performance; Lyapunov stability theory; asymptotic stability; bandwidth resource; distributed fault estimation; networked systems; quantization error; quantized measurements; sector bound approach; sufficient condition; Bandwidth; Design methodology; Estimation error; Linear matrix inequalities; Quantization (signal); Vectors; Channel resource limitation; Distributed fault estimation; Networked systems; Signal quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Automation (ICIA), 2014 IEEE International Conference on
Conference_Location :
Hailar
Type :
conf
DOI :
10.1109/ICInfA.2014.6932788
Filename :
6932788
Link To Document :
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