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Finite-time H∞ Filtering for Discrete-time Markovian Jump BAM Neural Networks with Time-varying Delays

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Abstract

This paper deals with the problem of finite-time H∞ filtering for discrete-time Markovian jump BAM neural networks with time-varying delays. To do this, firstly by choosing a suitable Lyapunov function and using Jensen inequality lemma, sufficient criteria are derived to guarantee that the resulting filtering error system is finite-time bounded. And then the gain matrices of the controller and filter are achieved by solving a feasibility problem in terms of linear matrix inequalities with a fixed parameter. Moreover, we assume that disturbances are described by the jumping parameters are generated from discrete-time homogeneous Markov process. Finally a numerical example is presented to show the effectiveness of the proposed method.

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Author information

Authors and Affiliations

  1. Department of Mathematics, Thiruvalluvar University, Vellore, 632 115, Tamilnadu, India

    M. Syed Ali & K. Meenakshi

  2. School of IT Information and Control Engineering, Kunsan National University, Kunsan, Korea

    Young Hoon Joo

Authors
  1. M. Syed Ali
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  2. K. Meenakshi
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  3. Young Hoon Joo
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Corresponding author

Correspondence to Young Hoon Joo.

Additional information

Recommended by Associate Editor Sung Jin Yoo under the direction of Editor Duk-Sun Shim. This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2016R1A6A1A03013567) and by the Korea Institute of Energy Technology Evaluation and Planning(KETEP) and the Ministry of Trade, Industry & Energy(MOTIE) of the Republic of Korea (No. 20174030201670).

M. Syed Ali graduated in 2002 and post-graduated in 2005 from Bharathiar University, India. He was conferred with Doctor of Philosophy in 2010 in Gandhigram Rural University, Gandhigram, India. Since March 2011 he is working as an Assistant Professor in Department of Mathematics, Thiruvalluvar University, Vellore, Tamil Nadu, India. He was awarded Young Scientist Award 2016 by The Academy of Sciences, Chennai. He has published more than 85 research papers in various SCI journals holding impact factors.

K. Meenakshi received the B.Sc. and M.Sc. from the Thiruvalluvar University, Tamil Nadu, India. Currently she is pursuing a Ph.D. degree under the supervision of an Assistant Professor Dr. M. Syed Ali, in Thiruvalluvar University, Tamil Nadu, India.

Young Hoon Joo received his B.S., M.S., and Ph.D. degrees in Electrical Engineering from Yonsei University, Korea, in 1982, 1984, and 1995, respectively. He worked with Samsung Electronics Company, Korea, from 1986 to 1995, as a Project Manager. He was with the University of Houston, Houston, TX, USA, from 1998 to 1999, as a Visiting Professor with the Department of Electrical and Computer Engineering. He is currently a Professor with the School of IT Information and Control Engineering, Kunsan National University, Korea. His major research interests include the field of intelligent robot, image precessing, intelligent control, human-robot interaction, wind-farm control, and intelligent surveillance systems. Dr. Joo served as the President for the Korea Institute of Intelligent Systems (KIIS, 2008-2009) and the Vice-President for the Korean Institute of Electrical Engineers (KIEE, 2013–2014, 2016) and the Editor-in- Chief for the International Journal of Control, Automation, and Systems (IJCAS, 2014 2017). And he is serving as the Director for Research Center of Wind Energy Systems funded by Korean Government (IJCAS, 2016 2023) and the President-Election of Korean Institute of Electrical Engineers (KIEE, 2018).

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Syed Ali, M., Meenakshi, K. & Joo, Y.H. Finite-time H∞ Filtering for Discrete-time Markovian Jump BAM Neural Networks with Time-varying Delays. Int. J. Control Autom. Syst. 16, 1971–1980 (2018). https://doi.org/10.1007/s12555-017-0632-y

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  • DOI: https://doi.org/10.1007/s12555-017-0632-y

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