2017
DOI: 10.22436/jnsa.010.04.53
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Stability analysis of delayed Takagi-Sugeno fuzzy systems: a new integral inequality approach

Abstract: This paper is concerned with the problem of the stability analysis for Takagi-Sugeno (T-S) fuzzy systems with interval time-varying delay. The delay is assumed to be differential with interval bounds, and has both the lower and upper bounds of the delay derivatives, in which the upper bound of delay derivative may be greater than one. By constructing some delaydependent Lyapunov functions, some stability criteria are derived by using the convex optimization method and new integral inequality techniques. Utiliz… Show more

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Cited by 13 publications
(2 citation statements)
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“…With the rapid growing of wireless communications technology, combination of multiple localization technologies system which can compensate and overcome the weaknesses in single location technology has become a popular proposal [21]. Fuzzy logic control is an adequate methodology for designing controllers to certain nonlinear systems [23] and has found numerous applications in a wide range of real engineering problems [24,25]. To overcome their individual limitations, by combining with GPS, WiFi, and CN positioning technology, a novel FLM is firstly proposed to enhance their individual positioning features.…”
Section: Our Contributionsmentioning
confidence: 99%
“…With the rapid growing of wireless communications technology, combination of multiple localization technologies system which can compensate and overcome the weaknesses in single location technology has become a popular proposal [21]. Fuzzy logic control is an adequate methodology for designing controllers to certain nonlinear systems [23] and has found numerous applications in a wide range of real engineering problems [24,25]. To overcome their individual limitations, by combining with GPS, WiFi, and CN positioning technology, a novel FLM is firstly proposed to enhance their individual positioning features.…”
Section: Our Contributionsmentioning
confidence: 99%
“…However, the emergence of fuzzy theory in the 19th century provided a good research direction for the processing and unification of data uncertainty. Moreover, fuzzy systems based on fuzzy theory have been continuously researched, which are widely used in many practical problems such as control engineering, pattern recognition, and artificial intelligence [6]. Compared with the previous deterministic description, fuzzy theory can describe the original data more naturally, furthermore, it has better advantages in dealing with the limitations of data and the robustness of noise [7].…”
Section: Introductionmentioning
confidence: 99%