• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.349-349
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• 2000

A Clustering Adaptive Fuzzy Logic Controller(CAFLC) is applied to the torque control of a brushless do motor drive. Objective of this system includes elimination of torque ripple due to cogging at low speeds under loads. The CAFLC implemented has advantages of computational simplicity, and self-tuning characteristics. Simulation results showed that the torque ripple and dynamic response of the system using a CAFLC were superior to the model reference adaptive controlled system.

• 전자공학회논문지S
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• 제35S권1호
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• pp.60-67
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• 1998

In this paper, a gain scheduling method of PID controller is proposed using fuzzy logic for balancing control of an inverted pendulum. First, gains of PID controller are calculated using pole-placement technique for the linearized model of an inverted pendulum and these gains are modified by fuzzy logic throughout control operations. A PD controller is used by switching near the set-point to improve the performance. It is illustrated by simulations that the proposed hybrid fuzzy control method yidels smaller rising time and overshoot compared to the fixed-gain PID controller or fuzzy logic-based only PID controller.

• Journal of Biosystems Engineering
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• 제25권2호
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• pp.107-114
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• 2000

Low temperature storage method is to increase the value of agricultural products by reducing quality loss and regulate consignment time by controlling respiration rates of agricultural products. Respiration rate of agricultural products depends on several factors such as temperature, moisture, gas composition and a microbe inside the storage room. Temperature is the most important factor among these, which affects respiration rate and causes low or high temperature damage. Fuzzy logic was used to control the temperature of a storage room ,which uses information of uncertain facts and mathematical model for room temperature control . Room temperature was controlled better by using fuzzy logic control method rather than on-off control method. Refrigerant flow rates and temperature deviations were measured for on-off system using TEV(temperature expansion valve) and for fuzzy system using EEV(Electrical Expansion Valve) . Temperature of the Storage room was lowered faster by using fuzzy system than on -off system. Temperature deviation was -0.6~+0.9$^{\circ}C$ for on-off system and $\pm$0.2$^{\circ}C$ for fuzzy system developed. Temperature deviation and variation of temperature deviation were used as inout parameters for fuzzy system. The most suitable input and output value were found by experiment. Cooling rate of the storage room decreased while temperature deviation increased for the sampling time of 20 sec.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권12호
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• pp.535-541
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• 2002

This paper proposes an adaptive fuzzy controller based fuzzy logic control for high performance of permanent magnet synchronous motor(PMSM) drive. In the proposed system, fuzzy control is sued to implement the direct controller as well as the adaptation mechanism. 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 adaptive fuzzy controller is evaluated by simulation for various operating conditions. The validity of the proposed controller is confirmed by performance results for PMSM drive system.

• 한국산업융합학회 논문집
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• 제24권6_1호
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• pp.645-658
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• 2021

In this paper, we propose a new approach to intelligent control based on fuzzy logic for work efficiency improvement of smart factory by the applicaion of ariticulated robot. The intelligent control that is applied to the working process by the joint of robotic manipulator is the main focus to improve a work efficiency for implimentation of smart factory in general manufacturing process. In this study, we propose a new method of a fuzzy model and then develop a nonlinear relationship between interaction forces and manipulator position using a fuzzy model. The reliability of the proposed control method is illustrated by simulation and experiments.

• 한국자동차공학회논문집
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• 제21권2호
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• pp.72-80
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• 2013

This study is to develop and evaluate an AFS and an ARS controllers to enhance lateral stability of a vehicle. A sliding mode control (SMC) and a fuzzy logic control (FLC) methods are applied to calculate the desired additional steering angle of AFS equipped vehicle or desired rear steer angle of ARS equipped vehicle. To validate AFS and ARS systems, an eight degree of freedom, nonlinear vehicle model and an ABS controllers are also used. Several road conditions are used to test the performances. The results showed that the yaw rate of the AFS and the ARS vehicle followed the reference yaw rate very well within the adhesion limit. However, the AFS improves the lateral stability near the limit compared with the ARS. Because the SMC and the FLC show similar vehicle responses, performance discrimination is small. On split-${\mu}$ road, the AFS and the ARS vehicle had enhanced the lateral stability.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권8호
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• pp.361-366
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• 2001

This thesis proposes a fuzzy logic cross coupled controller for a multi axis servo system. The overall control system consists of three elements: the axial position controller, the speed controller, and a fuzzy logic cross coupled controller. In conventional multi axis servo system, the motion of each axis is controlled independently without regard to the motion of other axes, in which the contour error, defined as the shortest distance between the desired and actual contours is compensated only by the position error of each axis. This decoupled control approach may result in degraded contouring performance due to such factors as mismatch of axial dynamics and axial loop gains. In practice, such systems contain many uncertainties, Therefore, the multi axis servo system must receive and evaluate the motion of all axes for a better contouring accuracy. Cross coupled controller utilizes all axis position error information simultaneously to produce accurate contours. However the existing cross coupled controllers cannot overcome friction, backlash and parameter variation. Also, since it is difficult to obtain an accurate mathematical model of multi axis system, here we investigate a fuzzy logic cross coupled controller method. Some simulations and experimental results are presented to illustrate the performance of the proposed controller.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.459-464
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• 1998

In this paper, we propose a stable fuzzy logic controller architecture for inverted pendulum,. In the design procedure, we represent the fuzzy system as a Takagi-Sugeno fuzzy model and construct a global fuzzy logic controller by considering each local state feedback controller and a supervisory controller, Unlike usual parallel distributed controller, one can design a global stable fuzzy controller without finding a common Lyapunov function by the proposed method. A simulation is performed to control the inverted pendulum to show the effectiveness and feasibility of the proposed fuzzy controller.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2000년도 학술대회논문집
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• pp.193-198
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• 2000

Switched reluctance motor drives have been finding their applications in the variable speed drives due to their relatively low cost, simple and robust structure, controllability and high efficiency. Fuzzy control does not need any model of plant. It is based on plant operator experience and heuristics. Fuzzy control is basically adaptive and gives robust performance for plant parameter variation. This paper deals with the sped control of switched reluctance motor using fuzzy controller with 7-rule based fuzzy logic. The proposed fuzzy controller is superior to the control performance of the conventional PI controller. The fuzzy controller is implemented by 80C196KC, 16 bit one-chip microcontroller.

• 한국지능시스템학회:학술대회논문집
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• 한국지능시스템학회 2008년도 춘계학술대회 학술발표회 논문집
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• pp.71-74
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• 2008

The main object of this paper is concentrated on distance control of two robot arms of a humanoid using Fuzzy Logic Controller (FLC) for handling a common object. Serial Link Robot arms are widely used in most significantly in Humanoids serving for older people and also in various industrial applications. A method is proposed here that separates the interconnections between two robot arms so that the resulting model of two arms is decomposed into fuzzy logic based controller. The distance between two end effectors is always kept equal to that of the diameter of an object to be handled, so that the object would not fall down. Mathematical model of this system was obtained to simulate the behavior of serial robotic arms in close loop control before using fuzzy logic controller. Lagrangian equation of motion has been used to obtain the appropriate mathematical model of Robotic arms. The results are shown to provide some improvement over those obtained by more conventional means.