• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.316-323
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• 2004

This paper deals with an $H_{\infty}$ output feedback controller design for singularly perturbed T-S fuzzy systems. It is shown that the $H_{\infty}$ norm of the singularly perturbed T-S fuzzy system is less than ${\gamma}$ for a sufficiently small ${\varepsilon}$>0 if the $H_{\infty}$ norms of both the slow and fast subsystem are less than ${\gamma}$. Using this fact, we develop a linear matrix inequality based design method which is independent of the singular perturbation parameter ${\varepsilon}$. A numerical example is provided to demonstrate the efficacy of the proposed design method.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.591-598
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• 2021

The digital phase-locked loops(DPLL) is a circuit used for phase synchronization and has been generally used in various fields such as communication and circuit fields. State estimators are used to design digital phase-locked loops, and infinite impulse response state estimators such as the well-known Kalman filter have been used. In general, the performance of the infinite impulse response state estimator-based digital phase-locked loop is excellent, but a sudden performance degradation may occur in unexpected situations such as inaccuracy of initial value, model error, and disturbance. In this paper, we propose a minimum variance finite impulse response filter with optimal horizon for designing a new digital phase-locked loop. A numerical method is introduced to obtain the measured value interval length, which is an important parameter of the proposed finite impulse response filter, and to obtain a gain, the covariance matrix of the error is set as a cost function, and a linear matrix inequality is used to minimize it. In order to verify the superiority and robustness of the proposed digital phase-locked loop, a simulation was performed for comparison and analysis with the existing method in a situation where noise information was inaccurate.