• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.423-429
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• 2011

This paper deals with the observer-based decentralized fuzzy controller design for nonlinear interconnected system for PEMFC. The nonlinear interconnected system is represented by a Takagi-Sugeno (T-S) fuzzy model. Based on T-S fuzzy interconnected system, the fuzzy observer and the decentralized fuzzy controller are designed. The stability condition of the closed-loop system with the proposed controller is represented to the linear matrix inequality (LMI) form, and the observer and control gain s are obtained by LMI. An example is given to show the verification discussed throughout the paper.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.451-456
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• 2015

In this paper, an observer-based decentralized fuzzy controller is designed for discrete-time interconnected fuzzy systems. Based on the fuzzy subsystem of the interconnected fuzzy system, the observer-based decentralized fuzzy controller is considered. By using the fuzzy subsystem and the observer-based decentralized fuzzy controller, the closed-loop system is obtained. From the closed-loop system, the stability condition with the maximum interconnection bound is developed, and its sufficient condition is represented as the linear matrix inequality (LMI). Finally, the numerical example is provided to verify the effectiveness of the proposed technique.

• Journal of Electrical Engineering and Technology
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• v.11 no.3
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• pp.724-732
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• 2016

In this paper, a sampled-data observer-based decentralized fuzzy control technique is proposed for a class of nonlinear large-scale systems, which can be represented to a Takagi-Sugeno fuzzy system. The premise variable is assumed to be measurable for the design of the observer-based fuzzy controller, and the closed-loop system is obtained. Based on an exact discretized model of the closed-loop system, the stability condition is derived for the closed-loop system. Also, the stability condition is converted into the linear matrix inequality (LMI) format. Finally, an example is provided to verify the effectiveness of the proposed techniques.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2393-2405
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• 2015

This paper considers a decentralized multiple faults detection and isolation (FDI) scheme for reconfigurable manipulators. Inspired by their modularization property, a global sliding mode (GSM) based stable adaptive fuzzy decentralized controller is investigated for the system in fault free, while for the system suffering from multiple faults (actuator fault and sensor fault), the decentralized sliding mode observer (DSMO) is employed to detect their occurrence. Hereafter, the time and location of faults can be determined by a fault isolation scheme via a bank of DSMOs. Finally, the effectiveness of the proposed schemes in controlling, detecting and isolating faults is illustrated by the simulations of two 3-DOF reconfigurable manipulators with different configurations successfully.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.437-443
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• 2015

This paper presents face recognition based on the fusion of visible image and thermal infrared (IR) texture estimated from the face image in the visible spectrum. The proposed face recognition scheme uses a multi- layer neural network to estimate thermal texture from visible imagery. In the training process, a set of visible and thermal IR image pairs are used to determine the parameters of the neural network to learn a complex mapping from a visible image to its thermal texture in the low-dimensional feature space. The trained neural network estimates the principal components of the thermal texture corresponding to the input visible image. Extensive experiments on face recognition were performed using two popular face recognition algorithms, Eigenfaces and Fisherfaces for NIST/Equinox database for benchmarking. The fusion of visible image and thermal IR texture demonstrated improved face recognition accuracies over conventional face recognition in terms of receiver operating characteristics (ROC) as well as first matching performances.