4.7 Article

Sampled-data H∞ filtering of Takagi-Sugeno fuzzy systems with interval time-varying delays

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jfranklin.2013.12.015

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资金

  1. Australian Research Council Discovery Projects [DP1096780]
  2. Research Advancement Awards Scheme Program at Central Queensland University, Australia
  3. Qianjiang Talent Project of Zhejiang Province of China [2010R10010]
  4. Natural Science Foundation of China [61074187, 60774058]

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The sampled-data H-infinity filtering for a continuous-time Takagi-Sugeno fuzzy system with an interval time-varying state delay is investigated, where the measurement outputs from the plant to the filter are assumed to be sampled at discrete instants with a variable period. Firstly, by means of a newly proposed inequality bounding technique and a new Lyapunov-Krasovskii functional, the fuzzy sampled-data H-infinity filtering performance analysis is carried out such that the resultant filter error system is asymptotically stable with a prescribed H-infinity attenuation performance index. Secondly, sufficient conditions on the existence of fuzzy sampled-data H-infinity filters are derived in the simultaneous presence of the time-varying state delay and the variable sampling period. The proposed bounding inequality lies in its more tightness and alleviates the enlargement of some inverse coefficients resulting from the utilization of the well-known Jensen integral inequality. Compared with some existing Lyapunov-Krasovskii functionals, more information about the relationship among the current state and its delayed state is considered. The upper bound of the derivative of the time-varying state delay is not required to be less than one. Different from some existing results in the literature, by applying the proposed results, each different value of such an upper bound (greater than one) leads to a different H-infinity disturbance attenuation level. Finally, a numerical example and a modified continuous stirred tank reactor system are given to show the effectiveness of the proposed results. (C) 2013 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

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