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howmuchinformationisneededinquantizednonlinearcontrol
Zheng Chuang1; Li Lin1; Wang Leyi2; Li Chanying3
2018
Source Publicationsciencechinainformationscience
ISSN1674-733X
Volume061Issue:009Pages:092205
AbstractQuantization rate is a crucial measure of complexity in determining stabilizability of control systems subject to quantized state measurements. This paper investigates quantization complexity for a class of nonlinear systems which are subjected to disturbances of unknown statistics and unknown bounds. This class of systems includes linear stablizable systems as special cases. Two lower bounds on the quantization rates are derived which guarantee input-to-state stabilizability for continuous-time and sampled-data feedback strategies, respectively. Simulation examples are provided to validate the results.
Language英语
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/48447
Collection系统科学研究所
Affiliation1.School of Mathematical Sciences,Beijing Normal University
2.Department of Electrical and Computer Engineering,Wayne State University
3.中国科学院数学与系统科学研究院
Recommended Citation
GB/T 7714
Zheng Chuang,Li Lin,Wang Leyi,et al. howmuchinformationisneededinquantizednonlinearcontrol[J]. sciencechinainformationscience,2018,061(009):092205.
APA Zheng Chuang,Li Lin,Wang Leyi,&Li Chanying.(2018).howmuchinformationisneededinquantizednonlinearcontrol.sciencechinainformationscience,061(009),092205.
MLA Zheng Chuang,et al."howmuchinformationisneededinquantizednonlinearcontrol".sciencechinainformationscience 061.009(2018):092205.
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