• Proceedings of the KIEE Conference
• /
• 1997.07b
• /
• pp.705-707
• /
• 1997

An optimal tuning algorithm of scaling factors is presented in this paper to automatically improve the performance of fuzzy controller. Especially, fuzzy controller has determined an moderate Scaling factor through trial and error. The presented method estimates automatically the optimal values of I/O scaling factors, using modified steepest descent method and this optimal tuning is for nonlinear input/output scaling factors. Simulation results verify the validity of the presented method.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.3004-3006
• /
• 2000

In this paper, we propose an optimal design method of Fuzzy-Neural Networks model with parallel structure for complex and nonlinear systems. The proposed model is consists of a multiple number of FNN connected in parallel. The proposed FNNs with parallel structure is based on Yamakawa's FNN and it uses simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rules. We use a HCM clustering and GAs to identify the structure and the parameters of the proposed model. Also, a performance index with a weighting factor is presented to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model. we use the time series data for gas furnace and the numerical data of nonlinear function.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.2473-2475
• /
• 2000

In this paper, we design a GA-fuzzy controller for position control and anti-swing at the destination point. Applied genetic algorithm is used to complement the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership function and control rules. Lagrange equation is used to represent the motion equation of trolley and load in order to obtain mathematical modelling.

• 제어로봇시스템학회:학술대회논문집
• /
• 1998.10a
• /
• pp.215-220
• /
• 1998

In order to optimize fuzzy model, we use the optimal algorithm with a hybrid type in the identification of premise parameters and standard least square method in the identification of consequence parameters of a fuzzy model. The hybrid optimal identification algorithm is carried out using a genetic algorithm and improved complex method. Also, the performance index with weighting factor is proposed to achieve a balance between the insults of performance for the training and testing data. Several numerical examples are used to evaluate the performance of the proposed model.

• Proceedings of the IEEK Conference
• /
• 2002.06a
• /
• pp.405-408
• /
• 2002

To support Internet traffic efficiently over ATM \networks, Guaranteed Frame Rate(GFR) has been proposed in tile ATM Forum to ensure minimum rate guarantees to VCs. In this paper, we proposed fuzzy logic based buffer management algorithm that provides MCR guarantee and fair sharing to GFR VCs. A key feature of proposed algorithm is its ability to accept or drop a new incoming packet dynamically based on buffer condition and load rate of VCs. This is achieved by using fuzzy logic controller for the production of a drop factor. Simulation result shows that proposed scheme significantly has improved fairness and TCP throughput compared with previous schemes.

• Proceedings of the IEEK Conference
• /
• 2000.07b
• /
• pp.1021-1024
• /
• 2000

In this paper, a neuro-fuzzy system for quantitative characterization of chaotic signals is proposed. The proposed system is differ from the previous methods in that the nonlinear functions of the nonlinear dynamical systems are calculated as the invariant factor. In the proposed neuro-fuzzy system, the nonlinear functions are determined by supervised learning. From the reconstructed nonlinear functions, the proposed system can generate extrapolated chaotic signals. This feature will help the study of nonlinear dynamical systems which require large number of chaotic data. To confirm the validity of the proposed system, nonlinear functions are reconstructed from 1-dimensional and 2-dimensional chaotic signals.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.1342-1345
• /
• 1993

In the cellular mobile communications as decreasing the cell radius to increse the reuse factor of frequencies, the handoff requests are increasing so that the efficient handoff decision making becomes a crucial problem. In this simulation study, we evaluate a set of handoff algorithms based on fuzzy-multicriteria decision making. These algorithms uses the parameters including the received signal strength intensity, the bit error rate and the distance between a mobile station and a base station. We compare the fuzzy algorithms in terms of call block ratio and handoff request ratio and call force ratio, and show the applicability of those algorithms in the cellular mobile communication systems.

• The KIPS Transactions:PartC
• /
• v.12C no.2 s.98
• /
• pp.229-234
• /
• 2005

We propose a fuzzy logic-based buffer management algorithm to improve internet traffic over ATM-GFR service. The proposed algorithm employs the strategies of early congestion detection and selective packet discard to achieve its design goals. A key feature of proposed algorithm is its ability to accept or drop a new incoming packet dynamically based on buffer condition and load rate of VCs. This is achieved by using fuzzy logic controller for the production of a drop factor. Simulation results show that proposed scheme significantly has improved fairness and TCP throughput compared with previous schemes.

• Industrial Engineering and Management Systems
• /
• v.7 no.1
• /
• pp.34-43
• /
• 2008

In recent years, many electronics producing firms have looked upon total quality management (TQM) strategy as a means by which they could maintain competitive advantage. This empirical research evaluates TQM strategic factors in order to determine the critical success factors in environmental uncertainty. Fuzzy analytic hierarchy process (FAHP) is the proposed research methodology to discuss and tackle the different decision criteria like effective leadership, people management, customer focus, strategic plan and process management, being involved in identifying the TQM strategic critical success factors with uncertainty. The result shows that effective leadership is the most critical success factor in TQM strategy.

• Journal of Power Electronics
• /
• v.8 no.2
• /
• pp.141-147
• /
• 2008

This paper deals with a new and improved control technique for shunt active filters (AF) used for compensating unwanted harmonic currents injected in the mains due to nonlinear varying loads. This work is motivated by the need to find a permanent solution to the rigorous hit and trial method for evaluating system parameters in an indirect control of AF. A fuzzy pre-compensated PI (Proportional-Integral) controller is used to fuzzify the reference DC voltage of AF to the controller input so that the overshoots and undershoots in its DC link voltage are minimized and the settling time is improved. A three-phase diode rectifier with R-L (Resistive-Inductive) load is used as a non-linear load to study the effectiveness of the proposed controller of the AF. Robustness to filter parameter variations, insensitivity to controller parameter variations, and transient response has been taken as performance evaluation parameters. The results are shown through simulations in Matlab using power system block sets to demonstrate the capability of the proposed controller of the AF.