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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.
A Local Influence Approach to Regression Diagnostics with Application to Robust Regression
Huh, Myung-Hoe,Park, Sung H. The Korean Statistical Society 1990 Journal of the Korean Statistical Society Vol.19 No.2
Regression diagnostics often involves assesment of the changes that result from deleting multiple cases. Diagnostic mehtodology based on global influence measure, however, needs prohibitive computing time. As an alternative, Cook (1986) developed influence approach in which it is checked whether a minor modification of specifiation influences key results of an analysis. In line with Cook's development, we propose and study an inflence derivative method that yields both the magnitude and direction of case influences. The utility of our methodology is highlighted when case influence derivatives are plotted in a lower demensional space. Such plots are especially effective in unmasking "masked" observations in least squares regression and in robust regression also. We give several illustrations.strations.
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 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/>
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
Development of 3D statistical mandible models for cephalometric measurements
Sung-Goo Kim,Won-Jin Yi,Soon-Jung Hwang,Soon-Chul Choi,Sam-Sun Lee,Min-Suk Heo,Kyung-Hoe Huh,Tae-Il Kim,Helen Hong,Ji Hyun Yoo 대한구강악안면방사선학회 2012 Imaging Science in Dentistry Vol.42 No.3
Purpose: The aim of this study was to provide sex-matched three-dimensional (3D) statistical shape models of the mandible, which would provide cephalometric parameters for 3D treatment planning and cephalometric measurements in orthognathic surgery. Materials and Methods: The subjects used to create the 3D shape models of the mandible included 23 males and 23 females. The mandibles were segmented semi-automatically from 3D facial CT images. Each individual mandible shape was reconstructed as a 3D surface model, which was parameterized to establish correspondence between different individual surfaces. The principal component analysis (PCA) applied to all mandible shapes produced a mean model and characteristic models of variation. The cephalometric parameters were measured directly from the mean models to evaluate the 3D shape models. The means of the measured parameters were compared with those from other conventional studies. The male and female 3D statistical mean models were developed from 23 individual mandibles, respectively. Results: The male and female characteristic shapes of variation produced by PCA showed a large variability included in the individual mandibles. The cephalometric measurements from the developed models were very close to those from some conventional studies. Conclusion: We described the construction of 3D mandibular shape models and presented the application of the 3D mandibular template in cephalometric measurements. Optimal reference models determined from variations produced by PCA could be used for craniofacial patients with various types of skeletal shape.