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최문경,허경회,이원진,오성욱,이삼선 대한구강악안면방사선학회 2008 Imaging Science in Dentistry Vol.38 No.1
The present study reports a case of eosinophilic granuloma of the mandibular condyle. Eosinophilic granulomas on the mandibular condyle are very rare, but there are several common clinical and radiographic presentations. The clinical presentations involve swelling on preauricular area, limitation of opening, TMJ pain, etc. The radiographic presentations involve radiolucent lytic condylar lesion with or without pathologic fracture. Sometimes new bone formations are observed. The purpose of the article is to add new cases to the literatures.
Robust Speed Sensorless Control of Induction Motors Using a Neural Network
Huh Sung-Hoe,Choy Ick,Park Gwi-Tae 전력전자학회 2004 ICPE(ISPE)논문집 Vol.- No.-
A robustly adaptive speed sensorless direct vector control system using a neural network (NN) is presented in this paper. Firstly, a new type of flux observer based on a robust control scheme is introduced. The uncertainty of the rotor resistance mainly affects the speed estimation performance, and until now, various observer approaches have been developed. The proposed flux observer employs an additional robustifying signal to cope with the uncertainty instead of the resistance adaptation procedure. The proposed adaptive scheme is determined so that the observer dynamics is stable in the sense of Lyapunov. Secondly, a robust speed controller using a NN is proposed. The lumped uncertainties including parametric uncertainty, external load disturbance and unmodeled dynamics are approximated by the NN, and an additional robust control term is introduced to compensate for the reconstruction error of the NN. A control law and adaptive laws for the weights in the NN and a bounding constant are established so that t closed-loop system is stable in the sense of Lyapunov. Some computer simulations are presented to show the efficiency of the proposed system.
A Neuro Fuzzy Controller for DC-DC Converters
Sung-hoe Huh,Yong-Ha Hwang,Gwi-Tae Park,Ick Choy 전력전자학회 1998 ICPE(ISPE)논문집 Vol.- No.-
A new type of controller for DC-DC converters is presented The proposed neuro-fuzzy controller combines fuzzy logic with neural networks to adjust parameters of the fuzzy controller to the most appropriate. Neither the exact mathematical models of the DC-DC converters nor the tuning process of the parameters of the fuzzy controller are needed in the proposed scheme Simulation results are presented to show the above process and transient, steady state responses, and load regulation of the given system.
Uncertainty Observer using the Radial Basis Function Networks for Induction Motor Control
Sung-Hoe Huh,Kuo-Beum Lee,Ick Choy,Gwi-Tae,Park,Ji-Yoon Yoo 전력전자학회 2004 JOURNAL OF POWER ELECTRONICS Vol.4 No.1
A stable adaptive sensorless speed controller for three-level inverter fed induction motor direct torque control (DTC) system using the radial-basis function network (RBFN) is presented in this paper Torque ripple in the DTC system for high power induction motor could he drastically reduced with the foregoing researches of switching voltage selection andtorque ripple reduction algorithms However, speed control performance is still influenced by the inherent uncertainty of the system such as parametric uncertainty, external load disturbances and unmodeled dynamics, and its exact mathematical model is much difficult to be obtained due to their strong nonlinearity. in this paper, the mherent uncertainty is approximated on-line by the RBFN, and an additional robust control tenn is introduced to compensate for the reconstruction error of the RBFN instead of the rich number of rules and additional updated parameters. Control law for stabilizing the system and adaptive laws for updating both of weights in the RBFN and a bounding constant are established so that the whole closed-loop system is stable in the sense of Lyapunov, and the stability proof of the whole control system is presented Computer simulations as well as experimental results are presented to show the validity and effectiveness of the proposed system
A Robust Sensorless Vector Control System for Induction Motors
Sung-Hoe Huh,Ick Choy,Gwi-Tae Park 전력전자학회 2001 ICPE(ISPE)논문집 Vol.2001 No.10
In this paper, a robust sensorless vector control system for induction motors with a speed estimator and an uncertainty observer is presented. At first, the proposed speed estimator is based on the MRAS(Mode Referece Adaptive System) scheme and constructed with a simple fuzzy logic(FL) approach The structre of the proposed FL estimator is very simple. The input of the FL is the rotor flux error difference between reference and adjustable model, and the output is the estimated incremental rotor speed. Secondly, the unmodeled uncertainties such as parametric uncertainties and external load disturbances are modeled by a radial basis function network(RBFN). In the overal speed control system, the control inputs are composed with a norminal control input and a compensated control input, which are from RBFN observer output and the modeling error of the RBFN, repectively. The compensated control input is derived from Lyapunov unction approach. The simulation results are presented to show the validity of the proposed system.<br/>
허명회,성내경,임용빈 한국품질경영학회 2005 품질경영학회지 Vol.33 No.1
For the count response we normally consider Poisson regression model. However, the conventional fitting algorithm for Poisson regression model is not reliable at all when the response variable is measured with sizable contamination. In this study, we propose an alternative fitting algorithm that is resistant to outlying values in response and report a case study in semiconductor industry.