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H ∞ Filtering in Mobile Sensor Networks with Missing Measurements and Quantization Effects

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Book cover Parallel Architecture, Algorithm and Programming (PAAP 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 729))

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Abstract

This paper is concerned with the \( {{H}_{\infty}} \) filtering problem for an array of 2D distributed parameter systems over lossy mobile sensor networks. The mobile sensor network suffers from missing measurements as well as quantization effects that are presented in a new framework. Bernoulli distribution is introduced to govern the data missing. A new \( {{H}_{\infty}} \) filtering technique is proposed for the addressed 2D semi-linear parabolic systems. Sufficient conditions are established in terms of some inequalities and the velocity law of each mobile sensor, such that the filtering error system is globally asymptotically stable in the mean square and has a guaranteed prescribed disturbance attenuation level \( \gamma \) for all nonzero noises. Finally, a numerical example is exploited to show the effectiveness of the proposed filtering scheme.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Nos. 61174021, 61104155).

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Authors and Affiliations

  1. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, 214122, China

    Xueming Qian & Baotong Cui

  2. School of Internet of Things Engineering, Jiangnan University, Wuxi, 214122, People’s Republic of China

    Xueming Qian & Baotong Cui

Authors
  1. Xueming Qian
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  2. Baotong Cui
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Corresponding author

Correspondence to Xueming Qian .

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Editors and Affiliations

  1. Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, China

    Guoliang Chen

  2. Sun Yat-sen University, Guangzhou, Guangdong, China

    Hong Shen

  3. Hainan University, Haikou, Hainan, China

    Mingrui Chen

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Qian, X., Cui, B. (2017). H ∞ Filtering in Mobile Sensor Networks with Missing Measurements and Quantization Effects. In: Chen, G., Shen, H., Chen, M. (eds) Parallel Architecture, Algorithm and Programming. PAAP 2017. Communications in Computer and Information Science, vol 729. Springer, Singapore. https://doi.org/10.1007/978-981-10-6442-5_26

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  • DOI: https://doi.org/10.1007/978-981-10-6442-5_26

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6441-8

  • Online ISBN: 978-981-10-6442-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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