• 한국지능시스템학회논문지
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• 제7권2호
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• pp.43-50
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• 1997

쓰러기 소각로는 다음과 같은 불명확한 요소들을 포함한다. 즉 연료로 사용되는 쓰레기의 물리적 특성의변동 그리고 연소현상의 복잡성 등이다. 이것은 기존의 제어기법을 쓰레기의 연소제어에 적용하기가 매우 어렵게 만든다. 따라서 대부분의 쓰레기 소각로는 조작자의 운전에 의존한다. 본 논문에서는 쓰레기 소각로의 연소제어를 위한 다변수퍼지모델 예측제어를 제안한다. 쓰레기 소각로의 모델을 구하기 위해 적응 네트워크에 기초한 퍼자추론시스템이 사용되고 동정된 퍼지 모델을 이용하여 다변수 퍼지모델 예측제어기가 설계된다. 그리고 제안된 제어기의 성능을 평가하기 위해 컴퓨터 시뮬레이션이 수행되었다.

• 제어로봇시스템학회논문지
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• 제19권9호
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• pp.791-796
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• 2013

This paper proposes a fuzzy logic gain scheduling method for depth controller of the AUV (Autonomous Underwater Vehicle). Gains of depth controller are calculated by using multi-loop root locus technique. Fuzzy logic based gain scheduling approach is used to modify multi-loop gains as control condition. It is illustrated by simulations that the proposed fuzzy logic gain scheduling method yields smaller rising time and overshoot compared to the fixed-gain controller. Finally, being implemented on real hardwares, all the proposed algorithms are validated with integrations of hardware and software altogether by HILS.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제9권2호
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• pp.76-82
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• 2009

A Heating, Ventilating and Air Conditioning (HVAC) system is a nonlinear multi-input multi-output (MIMO) system. This system is very difficult to control the temperature and the humidity ratio of a thermal space because of complex nonlinear characteristics. This paper proposes an adaptive fuzzy output feedback control based on observer for the nonlinear HVAC system. The nonlinear HVAC system is linearized through dynamic extension. State observers are designed for estimating state variables of the HVAC system. Fuzzy systems are employed to approximate uncertain nonlinear functions of the HVAC system with unavailable state variables. The obtained controller compares with an adaptive feedback controller. Simulation is given to demonstrate the effectiveness of our proposed adaptive fuzzy method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.780-785
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• 1992

We present a multi-sensor fusion method in positioning control of a robot by using fuzzy logic. In general, the vision sensor is used in the gross motion control and the force/torque sensor is used in the fine motion control. We construct a fuzzy logic controller to combine the vision sensor data and the force/torque sensor data. Also, we apply the fuzzy logic controller to the peg-in-hole process. Simulation results uphold the theoretical results.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권1호
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• pp.12-19
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• 2015

In order to guide the robots move along a collision-free path efficiently and reach the goal position quickly in the unknown multi-obstacle environment, this paper presented the navigation problem of a wheel mobile robot based on proximity sensors by fuzzy logic controller. Then a genetic algorithm was applied to optimize the membership function of input and output variables and the rule base of the fuzzy controller. Here the environment is unknown for the robot and contains various types of obstacles. The robot should detect the surrounding information by its own sensors only. For the special condition of path deadlock problem, a wall following method named angle compensation method was also developed here. The simulation results showed a good performance for navigation problem of mobile robots.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2016년도 전력전자학술대회 논문집
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• pp.519-520
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• 2016

BLSRM is a nonlinear, strong coupling and multi-variable system. The conventional control method is vulnerable to uncertain factors such as the load disturbance and satellite parameters change. It is difficult to obtain satisfactory control effect. Basing on a 8/10 BLSRM, whose suspending force control is separated with the torque control, this paper presents adaptive fuzzy PID controller for levitation control, which apply the fuzzy logic control to the conventional PID controller for parameters self-tuning. Both fuzzy and parameters of PID controller are self-tuning on-line, which improve the performance of controller. Finally, simulation and experimental results show the performance of the proposed method.

• 한국식품저장유통학회지
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• 제9권2호
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• pp.137-143
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• 2002

Temperature and humidity are the most important factors and should be effectively controlled for the cold storage of graius. Fuzzy logic can be easily implemented to the MIMO(Multi-Input Multi-Output) control systems. For the cold storage in grain bin, fuzzy logic was applied to an air conditioning system. The capacities of the grain bin and the air conditioner are 80 tons and 30㎾, respectively. Also, the target values of temperature and relative humidity in outlet duct of the air conditioner were 8$\^{C}$ and 75%, respectively. In order to control temperature and relative humidity of air, a damper in inlet duct was manipulated for temperature control and a heater was used for humidity control. Temperature deviation and change of temperature deviation were used as input parameters for the fuzzy system. Humidity was only considered as a load. The experimental results showed that the controlled temperature of exhausted air was maintained at 8$\pm$2$\^{C}$. Relative humidity of the air was also controlled at the target relative humidity of 50∼80%.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2009년도 추계학술대회 논문집
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• pp.355-358
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• 2009

This paper proposes efficiency optimization control of IPMSM drive using multi hybrid fuzzy controller(HFC). The design of the speed controller based on fuzzy-neural network that is implemented using fuzzy control and neural network. The design of the current based on HFC using model reference and the estimation of the speed based on neural network using ANN controller. In order to maximize the efficiency in such applications, this paper proposes the optimal control method of the armature current. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM The optimal current can be decided according to the operating speed and the load conditions. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using multi HFC. Also, this paper proposes speed control of IPMSM using HFC1, current control of HFC2-HFC3 and estimation of speed using ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled HFC, the operating characteristics controlled by efficiency optimization control are examined in detail.

• 조명전기설비학회논문지
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• 제23권10호
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• pp.59-68
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• 2009

유도전동기의 벡터제어는 고성능 적용에서 광범위하게 사용되고 있다. 그러나 이러한 드라이브 성능은 파라미터 변동에 의한 동조는 여전히 한계가 있다. 다양한 속도영역에서 운전하기 위하여 종래에는 PI과 같은 제어기를 보통 사용하였다. 이러한 제어기들은 이상적인 벡터제어 조건에서 광범위한 운전에 대하여 제한된 양호한 성능을 나타낸다. 본 논문은 다중 적응 제어기를 사용하여 유도전동기 드라이브의 고성능 제어를 제시한다. 이 제어기는 FAM(Fuzzy Adaptation Mechanism)에 의 해 속도제어, MFC(Model Reference Adaptive Fuzzy Control)에 의해 전류제어 그리고 ANN을 이용하여 속도추정을 수행한다. 제시한 제어 알고리즘은 FAD MFC및 ANN 제어기를 사용하여 유도전동기 드라이브 시스템에 적용한다. 제시한 제어기의 성능은 유도전동기의 파라미터를 사용하여 다양한 동작조건에서 해석으로 평가한다. 또한, 본 논문은 제어기의 효용성을 입증하기 위하여 해석결과를 제시한다.

• 한국지능시스템학회논문지
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• 제26권4호
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• pp.308-315
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• 2016

본 논문은 이산시간 장주기모델로 구성된 다개체시스템의 타카기-수게노(Takagi-Sugeno: T-S) 퍼지 군집제어 기법을 제안한다. 이산시간 모델은 오일러(Euler) 방법을 이용하여 유도한다. 이에 대한 T-S 퍼지 모델은 피드백 선형화 기법을 통해 구성하며, 이를 점근적으로 안정화하기 위한 퍼지제어기를 설계한다. 제어기 설계조건은 선형행렬부등식의 형태로 표현된다.