• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.2
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• pp.152-160
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• 2000

This paper addresses the analysis and design of fuzzy-model-based controller for nonlinear systems using extended PDC and optimal pole-placement schemes. In the design procedure, we represent the nonlinear system using a Takagi-Sugeno fkzy model and formulate the controller rules by using the extended parallel distributed compensator (EPDC) and construct an overall fuzzy logic controller by blending all local state feedback controllers with an optimal pole-placement scheme. Unlike the commonly used parallel distributed compensation technique, by blending a newly extended parallel distributed compensator and the optimal poleplacement schemes, we can design not only a local stable k z y controller but also an overall stable fuzzy controller to perform the tacking control objective. Furthermore, a stability analysis is carried out not only for the fuzzy model but also for a real nonlinear system. Finally. the effectiveness and feasibility of the proposed fizzy model-based controller design method has been shown through a simulation example.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.3
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• pp.111-119
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• 2002

This paper proposes a speed control system based on a fuzzy logic approach, integrated with a simple and effective adaptive algorithms. And this paper attempts to provide a thorough comparative insight into the behavior of induction motor drive with PI, direct and improved fuzzy speed controller. A indirect vector controlled induction motor is simulated under varying operating condition. The validity of the comparative results is confirmed by simulation results for induction motor drive system.

• Journal of the Korean Society of Industry Convergence
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• v.9 no.3
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• pp.173-178
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• 2006

For the design of multivariable fuzzy control systems decomposition of control rules is a efficent inference method since it alleviates the complexity of the problem. In some systems, however, inference error of the Gupta's decomposition method is inevitable because of its approximate nature. In this paper we define indices of applicability which decides whether the decomposition method can be applied to a multivariable fuzzy system or not.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.78-90
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• 2017

This paper presents the design of closed loop controllers operating a single-phase AC-DC three-level converter for improving power quality at AC mains. Closed loop inhibits outer voltage controller and inner current controller. Simulations of three level converter with three different voltage and current controller combinations such as PI-Hysteresis, Fuzzy-Hysteresis and Fuzzy tuned PI-Hysteresis are carried out in MATLAB/Simulink. Performance parameters such as input power factor and source current total harmonic distortion (THD) are considered for comparison of the three controller combinations. The fuzzy-tuned PI voltage controller with hysteresis current controller combination provides a better result, with a source-current THD of 0.93% and unity power factor without any source side filter for the three level converter. For load variations of 25% to 100%, a THD of less than 5% is obtained with a maximum value of only 1.67%. Finally, the fuzzy-tuned PI voltage with hysteresis controller combination is implemented in a Xilinx Spartan-6 XC6SLX25 FPGA board for experimental validation of power quality enhancement. A prototype 100 W, 0-24-48 V as output converter is considered for the testing of controller performance. A source-current THD of 1.351% is obtained in the experimental study with a power factor near unity. For load variations of 25% to 100%, the THD is found to be less than 5%, with a maximum value of only 2.698% in the experimental setup which matches with the simulation results.

• Proceedings of the KIEE Conference
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• 2004.04a
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• pp.143-146
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• 2004

This paper is proposed adaptive fuzzy-neural network(FNN) controller for speed control of induction motor drive. The design of this algorithm based on FNN controller that is implemented using fuzzy control and neural network. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive FNN controller is evaluated by analysis for various operating conditions.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.728-731
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• 1997

This paper proposes the systematic auto-tuning method for fuzzy controller using genetic algorithm(GA). In general, the design of fuzzy logic controller has difficulties in the acquisition of expert's knowledge and relies to a great extent on heuristic knowledge which, in many cases, cannot be objectively justified. So, the performance of the controller can be degraded in the case of plant parameter variations or unpredictable incident which the designer may have ignored. Proposed genetic algorithm searches the optimal rule structure, parameters of membership functions and scaling factors simultaneously and automatically by a new genetic coding format. Inverted pendrum system is provided to show the advantages of the proposed method.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1359-1361
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• 1996

This paper describes a design of real time fuzzy controller using Minimum fuzzy control Rule Selection Method(MRSM). The control algorithm of dynamic systems needs less computation time and memory. To reduce the computation time of fuzzy logic controller, minimum number of rules are to be selected for the fuzzy input variable. The universe of discourse is divided by the number of linguistic labels to allocate the assigned membership function to the fuzzy input variables. In this case, since fuzzy input variables are continuous, scale factor SU is tuned independently. According to increment of SU control surface is improved to adapt the change of system parameter. At this, crisp control surface is increased. With the increament of crisp control surface, fuzzy control surface is reduced. When error state deviates from desirable error state, crisp control surface is more useful than fuzzy control surface for obtaining fast rising time.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.5
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• pp.431-438
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• 2012

Non-linear turbojet engine controller with high operational performance has been designed for the high maneuverability UAV. The turbojet engine dynamic performance code has been developed to reflect the non-linear characteristics on controller design, by which the necessity of non-linear controller design was justified by investigating the limitation of linear model derived from the dynamic performance. The PI-like fuzzy controller was designed and enhanced by combining with conventional derivative control. This designed fuzzy controller proves its effectiveness by showing superior control performances over the conventional PID controller along with guaranteeing the safe operation within compressor surge, flame out and turbine temperature limits etc.

• Journal of Korean Association for Spatial Structures
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• v.15 no.4
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• pp.81-89
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• 2015

Damped outrigger systems have been proposed as a novel energy dissipation system to protect tall buildings from severe earthquakes and strong wind loads. In this study, semi-active damping devices such as magnetorheological (MR) dampers instead of passive dampers are installed vertically between the outrigger and perimeter columns to achieve large and adaptable energy dissipation. Control performance of semi-active outrigger damper system mainly depends on the control algorithm. Fuzzy logic control algorithm was used to generate command voltage sent to MR damper. Genetic algorithm was used to optimize the fuzzy logic controller. An artificial earthquake load was generated for numerical simulation. A simplified numerical model of damped outrigger system was developed. Based on numerical analyses, it has been shown that the semi-active damped outrigger system can effectively reduce both displacement and acceleration responses of the tall building in comparison with a passive outrigger damper system.

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