• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.577-582
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• 1999

Using a sole input variable simplifies the design process for the fuzzy logic controller(FLC). This is called single-input fuzzy logic controller(SFLC). However it is still deficient in the capability of adapting to the varying operating conditions. We here design a single-input adaptive fuzzy logic controller(AFLC) using a switching function of the sliding mode control. The AFLC can directly incorporate linguistic fuzzy control rules into the controller. Hence some parameters of the membership functions characterizing the linguistic terms of the fuzzy rules can be adjusted by an adaptive law. In the proposed AFLC center values of fuzzy sets are directly adjusted by a fuzzy logic system. We prove that 1) its closed-loop system is globally stable in the sense that all signals involved are bounded and 2)its tracking error converges to zero asymptotically. We perform computer simulation using a nonlinear plant.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.16-21
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• 2008

In order to protect the environment from the refrigerant pollution, the $CO_2$ may be regarded as one of the most attractive alternative refrigerants for an automotive air-conditioning system. Control methods for a $CO_2$ system should be different because of $CO_2$'s unique properties as a refrigerant. Especially, the high-side pressure of a $CO_2$ system should be controlled for the effective operation of the system. High-side pressure algorithms, which were composed of the pressure setpoint algorithm and the pressure setpoint reset algorithm, were developed. Pressure setpoint algorithms, by using a neural network and by using a least square method, were developed and compared. Pressure setpoint reset algorithms, by using a fuzzy logic and by using a proportional logic, were also developed and compared. Simulation results showed that a least square method was more useful than a neural network for the pressure setpoint algorithm. And a proportional logic was more practical than a fuzzy logic for the pressure setpoint reset algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.33-38
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• 1999

This paper proposes a translation approach for PLCs (Programmable logic controllers) converting ladder diagrams directly to native codes, and describes detailed steps of the method followed by performance evaluation. A general-purpose DSP (Digital signal processor) based implementation validates the approach as well. A benchmark test shows that the Proposed translation framework fairly speeds up execution in comparison with the existing interpretation approach.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2258-2263
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• 2003

This paper presents the design and development of an optimal fuzzy logic controller (FLC) for a laser tracking system. An optimal intelligent fuzzy logic controller was founded on integral criterion of the fuzzy models and three-dimensional fuzzy control. Research had been also concentrated on the methods for multivariable fuzzy models for the purposes of real-time process. Simulation results have shown remarkable tracking performance of this fuzzy PID controller.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.234-239
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• 2009

In this article we present the simulation results of induction motor speed regulation by direct torque control with a classic PI regulator. The MATLAB Simulink programming environment is used as a simulation tool. The results obtained, using a fuzzy logic, shows the importance of this method in the improvement of the performance of such regulation.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.749-751
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• 1999

We acquired operating data in an existing steam turbine power plant using analog control system to investigate operation characteristics. We analyzed a load control logic to develop a digital turbine control system. The load control logic is constituted of load target, load reference, loading rate, load limit and admission mode transfer of valve. The result of this paper is utilized to implement a digital turbine control system.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.911-916
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• 1991

Spent nuclear fuel is highly radioactive and requires remote operation due to radiation exposure. Motors which have been used in the highly radioactive environments are a DC type because of their easy implementation on control system. However there are some problems such as mechanical maintenance of brush and commutator, high cost, and heavy material control. AC servo motors are applied and tested on fuzzy and conventional control algorithms. Fuzzy logic controls of AC servo give adequate control accuracy and power for spent fuel handling in radioactive environments.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1483-1486
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• 2002

In this paper, a new scheme of iterative loaming control of a robot manipulator is presented. The proposed method uses a fuzzy sliding mode controller(FSMC), which is designed based on the similarity between the fuzzy logic control(FLC) and the sliding mode control(SMC), for the feedback. With this, the proposed method makes possible fDr fast iteration and has advantages that no linear approximation is used for the derivation of the learning law or in the stability proof Full proof of the convergence of the fuzzy sliding base learning scheme Is given.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.4
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• pp.1850-1858
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• 2014

The object of this study is to develop an cooling control algorithm for electronics devices of the electric vehicle. In order to estimate the existing cooling control logic of the electronic devices for the small and medium sized electric vehicle, the experiments on the coolant temperature variation of the cooling system were conducted under 4 different seasons conditions. As a result, the existing cooling control logic were overcooled when it was compared with the reference temperature for a required cooling load. In addition, the newly developed optimum cooling control logic for improving the mileages of the tested electric vehicle with consideration of the ambient temperature, vehicle speed, and refrigerant temperature of the air conditioning on/off is necessary.

• Smart Structures and Systems
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• v.12 no.6
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• pp.595-617
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• 2013

Semi-active control equipments are used to effectually enhance the seismic behavior of structures. Magneto-rheological (MR) dampers are semi-active devices that can be utilized to control the response of structures during seismic loads and have received voracious attention for response suppression. They supply the adaptability of active devices and stability and reliability of passive devices. This paper presents an optimal fuzzy logic control scheme for vibration mitigation of buildings using magneto-rheological dampers subjected to near-fault ground motions. Near-fault features including a directivity pulse in the fault-normal direction and a fling step in the fault-parallel direction are considered in the requisite ground motion records. The membership functions and fuzzy rules of fuzzy controller were optimized by genetic algorithm (GA). Numerical study is performed to analyze the influences of near-fault ground motions on a building that is equipped with MR dampers. Considering the uncontrolled system response as the base line, the proposed method is scrutinized by analogy with that of a conventional maximum dissipation energy (MED) controller to accentuate the effectiveness of the fuzzy logic algorithm. Results reveal that the fuzzy logic controllers can efficiently improve the structural responses and MR dampers are quite promising for reducing seismic responses during near-fault earthquakes.