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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Journal of Korean Institute of Intelligent Systems
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Korean Institute of Intelligent Systems
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Volume & Issues
Volume 8, Issue 6 - Nov 1998
Volume 8, Issue 5 - Oct 1998
Volume 8, Issue 4 - Aug 1998
Volume 8, Issue 3 - Jun 1998
Volume 8, Issue 2 - Apr 1998
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Notes on Locally Convex Fuzzy Topological Vector Spaces Gil Seob Rhie and In Ah Hwang
Journal of Korean Institute of Intelligent Systems, volume 8, issue 5, 1998, Pages 1~4
The main goal of this paper is to investigate some properties of the locally convex fuzzy topological vector space.
A Suitable Fuzzy controller for DC-DC Converters
Journal of Korean Institute of Intelligent Systems, volume 8, issue 5, 1998, Pages 5~13
In this paper, a fuzzy controller for DC-DC converters is proposed in order to obtain good performances that can not be achieved by liner control techniques in the presence of wide parameter variz. tions. The presented approach is general and can he applied to any DC-DC converter topologies. While the conventional method uses error and derivative of error, the proposed controller method uses state variables. Such method is very efficient in case of DC-DC converters and can guaranlee both stable small-signal responses and improved large-signal responses. Application results of boost converter(booster) show control potentialities.
A Study on Fuzzy Comparisons between Fuzzy Numbers Based on the Satisfaction Function
Journal of Korean Institute of Intelligent Systems, volume 8, issue 5, 1998, Pages 14~20
This paper proposes a fuzzy comparison method called the fuzzy satisfaction function. It compares two fuzzy numbers and produces a fuzzy set on [O, 11 as the comparison result. It represents the possibility that a fuzzy number is greater(smal1er) than the other with a fuzzy set on [0, I]. It is extended from the satisfaction function which compares two fuzzy numbers and generates a value in [0, 11 as the result. This paper summarizes the satisfaction function and proposes the fuzzy satisfaction function. Some numerical examples are also presented in this paper.
Design of a Variable Structure Controller with Nonlinear Fuzzy Sliding Surgaces
Journal of Korean Institute of Intelligent Systems, volume 8, issue 5, 1998, Pages 21~28
This study develops a variable structure controller using the time-varying nonlinear sliding surface instead of the fixed sliding surface, which has been the robustness against parameter variations and extraneous disturbance during the reaching phase. By appling TS fuzzy algorithm to the regulation of the rionlinear sliding surface, the reaching time of the system trajectory is faster than the fixed method. This proposed scheme has better performance than the conventional method in reaching time, parameter variation and extraneous disturbance. To demonstrate its performance, the proposed control algorithm is applied to a rotational inverted pendulum.
A Study on the Load Frequency control of Power System Using Neural Network Self Tuning PID Controller
Journal of Korean Institute of Intelligent Systems, volume 8, issue 5, 1998, Pages 29~38
This paper proposes the neural network self-tuning PID controller for the load frequency control of 2- areas power system, namely, the prompt convergence of frequency and tie-line power flow deviation. The neural network applied to computer simulation consists of neurons of two inputs, ten hiddens and tliree outputs layer. Neurons of two inputs layer receive the error and its change rate of the system and cutputs layer consists of three neurons for the parameters of the PID controller. The simulation results shows that the proposed neural network self-tuning PID controller is superior to conventional control t~:chniques(Optimal, PID) in dynamic response and control performance.
Position Compensation of a Mobile Robot Using Neural Networks
Journal of Korean Institute of Intelligent Systems, volume 8, issue 5, 1998, Pages 39~44
Determining the absolute location of a mobile robot is essential in the navigation of a mobile robot. In this paper, a method to determine the position of a mobile robot through the visual image of a landrnark using neural networks is proposed. In determining the position of a mobile robot on the world coordinate, there is a position error because of uncertainty in pixels, incorrect camera calibration and lens distortion. To reduce the errors, a method using a BPNN(Back Propagation Neural Network) is proposed. The experimental results are presented to illustrate the superiority of the proposed method when comparing with the conventional methods.
3-Dimensional Free Form Design Using an ASMOD
Journal of Korean Institute of Intelligent Systems, volume 8, issue 5, 1998, Pages 45~50
This paper presents the process generating the 3-dimensional free f o r m hull form by using an ASMOD(Adaptive Spline Modeling of Observation Data) and a hybrid curve approximation. For example, we apply an ASMOD to the generation of a SAC(Sectiona1 Area Curve) in an initial hull form design. That is, we define SACS of real ships as B-spline curves by a hybrid curve approximation (which is the combination method of a B-spline fitting method and a genetic algorithm) and accumulate a database of control points. Then we let ASMOD learn from the correlation of principal dimensions with control points and make the ASMOD model for SAC generation. Identically, we apply an ASMOD to the generation of other hull form characteristic curves - design waterline curve, bottom tangent line, center profile line. Conclus~onally we can generate a design hull form from these hull form characteristic curves.
Design of Stabilizing Takagi-Sugeno Fuzzy Controllers - An LIM Approach
Journal of Korean Institute of Intelligent Systems, volume 8, issue 5, 1998, Pages 51~60
There have been several recent studies concerning the stability of fuzzy control system and the synthesis of stabilizing fuzzy controllers. This paper reports on a related study nf the TS (Takagi-Sugeno) fuzzy systems, and it is shown that the controller synthesis problems for the nonlinear systems described by the TS fuzzy model can be reduced to convex problems involving LMIs (linear matrix ineclualities). After classifying the TS fuzzy systems into three families based on how diverse their input matrices are, different controller synthesis procedure is given for each of these families. A numerical example is presented to illustrate the synthesis procedures developed in this paper.
Parallel Genetic Algorithm based on a Multiprocessor System FIN and Its Application to a Classifier Machine
Journal of Korean Institute of Intelligent Systems, volume 8, issue 5, 1998, Pages 61~71
Genetic Algorithm(GA) is a method of approaching optimization problems by modeling and simulating the biological evolution. GA needs large time-consuming, so ti had better do on a parallel computer architecture. Our proposed system has a VLSI-oriented interconnection network, which is constructed from a viewpoint of fractal geometry, so that self-similarity is considered in its configuration. The approach to Parallel Genetic Algorithm(PGA) on our proposed system is explained, and then, we construct the classifier system such that the set of samples is classified into weveral classes based on the features of each sample. In the process of designing the classifier system, We have applied PGA to the Traveling Salesman Problem and classified the sample set in the Euclidean space into several categories with a measure of the distance.
Fuzzy Logic Based Relaying Using Flux-differential Current Derivative Cure for Power Transformer Protection
Journal of Korean Institute of Intelligent Systems, volume 8, issue 5, 1998, Pages 72~82
Power transformer protective relay should block the tripping during magnetizing imrush and rapidly operate the tripping during internal faults. But traditional approaches maloperate in the case of magnetizing inrush with low second harmonic component and internal faults with high second harmounic component. To enhance the fault detection sensitivities of conventional technuques, flux-differential current derivative curve by fuzzy theory approaches is used. This paper deals with fuzzy logic based protective relaying for power transformer. The proposed fuzzy based relaying algorithm consisits of flux-differential current derivative curve, harmonics restraint, and precentage differential characteristic curv. The proposed relaying was tested with relaying signals obtained from Salford EMTP simulation package and showed a fast and accurate trip operation.
FADIS : An Integrated Development Environment for Automatic Design and Implementation of FLC
Journal of Korean Institute of Intelligent Systems, volume 8, issue 5, 1998, Pages 83~97
This paper developes an integrated environment CAD system that can design and implement an accurate and cost-effective FLC automatically. For doing this, an integrated development environment (IDE) (called FADIS; FLC Automatic Design and Implementation Station) is built by the seemless coupling of many existing. CAD tools in an attempt to the FADIS performs various functions such that (1) i~utomatically generate the VHDL components appropriate for the proposed FLC architecture from the various design parameters (2) simulate the generated VHDL code on the Synopsys's VHDL Simulator, (3) automatically compiler, (4) generate the optimized, placed, and routed rawbit files from the synthesized modules by Xilinx's XactStep 6.0, (5) translate the rawbit files into the downloadable ex- [:cution reconfigurable FPGA board (VCC's EVCI), and (7) continuously monitor the control status graphically by communicating the FLC with the controlled target via S-bus. The developed FADIS is tested for its validity by carrying out the overall procedures of designing and implementing the FLC required for the truck-backer upper control, the reduction of control execution time due to the controller's FPGA implementation is verified by comparing with other implementations.
An Efficient Traning of Multilayer Neural Newtorks Using Stochastic Approximation and Conjugate Gradient Method
Journal of Korean Institute of Intelligent Systems, volume 8, issue 5, 1998, Pages 98~106
This paper proposes an efficient learning algorithm for improving the training performance of the neural network. The proposed method improves the training performance by applying the backpropagation algorithm of a global optimization method which is a hybrid of a stochastic approximation and a conjugate gradient method. The approximate initial point for f a ~gtl obal optimization is estimated first by applying the stochastic approximation, and then the conjugate gradient method, which is the fast gradient descent method, is applied for a high speed optimization. The proposed method has been applied to the parity checking and the pattern classification, and the simulation results show that the performance of the proposed method is superior to those of the conventional backpropagation and the backpropagation algorithm which is a hyhrid of the stochastic approximation and steepest descent method.