详细信息

QUANTIZED H CONTROL FOR NETWORKED SYSTEMS WITH COMMUNICATION CONSTRAINTS  ( SCI-EXPANDED收录)  

文献类型:期刊文献

英文题名:QUANTIZED H CONTROL FOR NETWORKED SYSTEMS WITH COMMUNICATION CONSTRAINTS

作者:Yan, Huaicheng[1,2];Shi, Hongbo[1,2];Zhang, Hao[3,4];Yang, Fuwen[1,2]

机构:[1]E China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]E China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China;[3]Tongji Univ, Dept Control Sci & Engn, Shanghai 200092, Peoples R China;[4]City Univ Hong Kong, Dept Mech & Biomed Engn, Kowloon, Hong Kong, Peoples R China

年份:2013

卷号:15

期号:5

起止页码:1468

外文期刊名:ASIAN JOURNAL OF CONTROL

收录:;WOS:【SCI-EXPANDED(收录号:WOS:000324930700022)】;

基金:This work is supported by National Natural Science Foundation of China (61004028, 61272064, 61273026, 61174064), Fundamental Research Funds for Central Universities, Xiangjiang Project (XJ2011023), Innovation Program of Shanghai Municipal Education Commission (12zz052), and China Postdoctoral Science Foundation funded project (2012M520048).

语种:英文

外文关键词:H control; networked control system; quantization; time-varying delay; multiple packet dropouts

摘要:The problem of quantized H control for networked control systems (NCSs) subject to time-varying delay and multiple packet dropouts is investigated in this paper. Both the control input and the measurement output signals are quantized before being transmitted and the quantized errors are described as sector bound uncertainties. The measurement channel and the control channel packet dropouts are considered simultaneously, and the stochastic variables satisfying Bernoulli random binary distribution are utilized to model the random multiple packet dropouts. Sufficient conditions for the existence of an observer-based controller are established to ensure the exponential mean-square stablility of the closed-loop system and achieve the optimal H disturbance attenuation level. By using a globally convergent algorithm involving convex optimization, the nonconvex feasibility can be solved successfully. Finally, a numerical example is given to illustrate the effectiveness and applicability of the proposed method.

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