• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.408-411
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• 1993

In this paper, we propose the Fuzzy Neural Controller with a Self-Organizing Map based on the fuzzy relation neuron. The fuzzy ndes expressing the input-output relation of the system are obtained by using the fuzzy relation neuron and updated automatically by means of the generalized delta rule. Also, the proposed method has a capability to express the knowledge acquired from the input-output data in form of fuzzy inferences rules. The learning algorithm of this fuzzy relation neuron is described. The effectiveness of the proposed fuzzy neural controller is illustrated by applying it to a number of test data sets.

• Smart Structures and Systems
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• v.20 no.3
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• pp.285-301
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• 2017

This paper presents the design and the application of a new self-powered hybrid electromagnetic damper that can harvest energy while mitigating the vibration of a structure. The damper is able to switch between an energy harvesting passive mode and a semi-active mode depending on the amount of energy harvested and stored in the battery. The energy harvested in the passive mode resulting from the suppression of vibration is employed to power up the monitoring and electronic components necessary for the semi-active control. This provides a hybrid control capability that is autonomous in terms of its power requirement. The proposed hybrid circuit design provides two possible options for the semi-active control: without energy harvesting and with energy harvesting. The device mechanism and the circuitry that can drive this self-powered electromagnetic damper are described in this paper. The parameters that determine the device feasible force-velocity region are identified and discussed. The effectiveness of this hybrid damper is evaluated through a numerical simulation study on vibration mitigation of a bridge stay cable under wind excitation. It is demonstrated that the proposed hybrid design outperforms the passive case without external power supply. It is also shown that a broader force range, facilitated by decoupled passive and semi-active modes, can improve the vibration performance of the cable.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2849-2852
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• 1999

This paper describes the fuzzy PD controller using simplified indirect inference method. First, the fuzzy PD controller is derived from the conventional continuous time linear PD controller. Then the fuzzification, control-rule base, and defuzzification using SIIM in the design of the fuzzy controller are discussed in detail. The resulting controller is a discrete time fuzzy version of the conventional PD controller. which has the same linear structure. but are nonlinear functions of the input signals. The proposed controller enhances the self-tuning control capability. particularly when the process to be controlled is nonlinear. As the SIIM is applied, the fuzzy Inference results can be calculated with splitting fuzzy variables into each action component and are determined as the functional form of corresponding variables. So the Proposed method has the capability of the high speed inference and extending the fuzzy input variables easily. Computer simulation results have demonstrated the superior to the control Performance of the one Proposed by D. Misir et at. Final)y. we simulated the contour control of the X-Y tables with direct control strategies using the proposed fuzzy PD controller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.122-129
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• 2008

The direct torque control method of an inverter fed squirrel cage typed induction motor using fuzzy logic controller has been proposed. This method is suitable for the traction which requires a fast torque response during the star-up and step change. The fuzzy control algorithm based upon the control principles of conventional DSC(Direct Self Controller) is developed. The fuzzy algorithm is tarried out by defuzzification strategy of the fuzzy output extracted from the possibility distribution of an inferred fuzzy control rule. The flux and torque of an induction motor are estimated by the dynamic model of the rotor flux field-oriented scheme which has decoupling characteristics and excellent dynamic response over a wide speed range. The proposed controller shows a good dynamic response. Moreover, since the fuzzy controller possesses highly adaptive capability, the performance of fuzzy controller is quite robust and insensitive to the motor parameters and change of operation conditions.

• Smart Structures and Systems
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• v.15 no.4
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• pp.1103-1120
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• 2015

A self-sensing magnetorheological (MR) damper with embedded piezoelectric force sensor has recently been devised to facilitate real-time close-looped control of structural vibration in a simple and reliable manner. The development and characterization of the self-sensing MR damper are presented based on experimental work, which demonstrates its reliable force sensing and controllable damping capabilities. With the use of experimental data acquired under harmonic loading, a nonparametric dynamic model is formulated to portray the nonlinear behaviors of the self-sensing MR damper based on NARX modeling and neural network techniques. The Bayesian regularization is adopted in the network training procedure to eschew overfitting problem and enhance generalization. Verification results indicate that the developed NARX network model accurately describes the forward dynamics of the self-sensing MR damper and has superior prediction performance and generalization capability over a Bouc-Wen parametric model.

• Proceedings of the KIEE Conference
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• 1999.07f
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• pp.2783-2785
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• 1999

A fast switching gate driver suitable for high performance self resonant electronic ballasts is presented. The proposed gate driver has negligible switching loss and driving loss owing to pnpn structure and zero voltage switching( ZVS ); moreover, the gate driver has frequency control capability. Therefore, a self resonant inverter using proposed gate driver can operate as external exciting resonant inverters. The experiments confirm that the proposed gate driver perform the desired operations over full power control range for 40W fluorescent lamp electronic ballast.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.35-41
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• 2000

This paper describes the design of fuzzy digital PID controller using a simplified indirect inference method. First, the fuzzy digital PID controller is derived from the conventional continuous-time linear digital PID controller,. Then the fuzzification, control-rule base, and defuzzification using SIM in the design of the fuzzy controller are discussed in detail. The resulting controller is a discrete-time fuzzy version of the conventional PID controller, which has the same linear structure, but are nonlinear functions of the input signals. The proposed controller enhances the self-tuning control capability, particularly when the process to be controlled is nonlinear. When the SIIM is applied the fuzzy inference results can be calculated with splitting fuzzy variables into each action component and are determined as the functional form of corresponding variables. So the proposed method has the capability of the high speed inference and adapting with increasing the number of the fuzzy input variables easily. Computer simulation results have demonstrated that the proposed method provides better control performance than the one proposed by D. Misir et al.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2898-2901
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• 1999

This paper describes the design of nonlinear fuzzy I+PD controller using simplified indirect inference method. First, the fuzzy I+PD controller is derived from the conventional continuous time linear I+PD controller. Then the fuzzification, control-rule base, and defuzzification using SIIM in the design of the fuzzy controller are discussed in detail. The resulting controller is a discrete time fuzzy version of the conventional I+PD controller. which has the same linear structure. but are nonlinear functions of the input signals. The proposed controller enhances the self-tuning control capability. Particularly when the process to be controlled is nonlinear When the SIIM is applied, the fuzzy inference results can be calculated with splitting fuzzy variables into each action component and are determined as the functional form of corresponding variables. So the proposed method has the capability of the high speed inference and adapting with increasing the number of the fuzzy input variables easily. Computer simulation results have demonstrated the superior to the control performance of the one Proposed by D. Misir et at.

• Korean Journal of Community Nutrition
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• v.21 no.6
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• pp.497-508
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• 2016

Objectives: The purpose of this study was to evaluate the effect of nutrition education using materials based on social cognitive theory. Education topics focused on improving health-related and dietary self-awareness and behavior capability in adolescents. Methods: Participants were recruited from a middle school for girls; 67 students (educated group, n=34 and control group, n=33) participated. The education group received 12 lessons in club activity class. Self-administered surveys were conducted for each group before and after the nutrition education program. The questionnaires consisted of variables such as self-efficacy, outcome expectation, outcome expectancy, knowledge, and dietary practices based on the social cognitive theory. Education satisfaction was evaluated using a five-point Likert scale for two sections: a) teaching and learning and b) education results. The data were analyzed using a t-test and Chi Square-test (significance level: p < 0.05). Results: In the education group, post-education, there were significant differences in self-efficacy (p < 0.05), knowledge (p < 0.01), and dietary practices (p < 0.05), whereas outcome expectation and expectancy did not show any significant differences. None of the variables showed any significant differences in the control group. Educational satisfaction scores were $4.38{\pm}0.12$ (teaching and learning) and $4.14{\pm}0.15$ (education results). Conclusions: This study showed that improving adolescent's awareness and behavior capability has a positive effect on their dietary practices. Moreover, this study suggested that a theory-based determinant should be considered to improve dietary behavior among adolescents.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.3
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• pp.17-27
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• 1996

More fuzzy hardware are expected to be utilized in the future to construct fuzzy logic controllers (FLCs). It is hard to find an existing fuzzy hardware which is adopting advanced functions such as self-tuning algorithm in addition to the conventional inference calculation. That is mainly because conventional self-tuning algorithms designed to implement with some hardware circuits is required for fuzzy hardwares to have self-tuning capability. As a first step toward the feature, a novel self-tuning algorithm is proposed in this paper. Based on the search method, the main idea of the proposed algorithm is to detemine valid ranges of input variables of an FLC in order to maximize performance indices fo the control system. The performance indices are so ismple as to be realized by hardware circuit. in dadditon to the conventional scaling-factor adjustment, the algorithm adjusts offset values as well, which, in effect, modifies fuzzy rules of the FLC. To justify the performance of the proposed algorithm, a simulation study is executed.