• Journal of agriculture & life science
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• v.44 no.4
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• pp.69-77
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• 2010

Fuzzy control is widely used for improving temperature control performance as controlling ventilation in greenhouse because the technique can respond more flexibly to the outside air temperature and wind speed. By pre-studied PID and normal fuzzy control this study was performed to obtain the fundamental data that can be established in better greenhouse ventilation control method. The temperature control error by the simple fuzzy control was $1.2^{\circ}C$. The accumulated operating size of the window and the number of operating were 84% and 13, respectively. These showed equivalent control performance with pre-studied result that control error. The accumulated operating size of the window and the number of operating were 75% and 12, respectively. The proposed fuzzy technique was simple control logic method compared with step and PID control methods, but it showed equivalent performance. Therefore, the proposed simple fuzzy control method could be used in micro controller of small programmable memory size and many applications.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2120-2122
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• 2002

There are several types of control systems that use fuzzy logic controller as a essential system component. The majority of research work on fuzzy PID controller focuses on the conventional two-input PI or PD type controller. However, fuzzy PID controller design is a complex task due to the involvement of a large number of parameters in defining the fuzzy rule base. In this paper we combined conventional PI type and PD type fuzzy controller and set the initial parameters of this controller from the conventional PID controller gains obtained by Ziegler-Nichols tuning or other coarse tuning methods. After that, by replacing some of these parameters with sing1e neurons and making them to be adjusted by back-propagation learning algorithm we designed a neuro-fuzzy controller which showed good performance characteristics in both computer simulation and actual application.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.1
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• pp.55-64
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• 2002

Due to the friction characteristics of cylinders and the rail of a passenger car, in the system actuated with hydraulic systems, there exist dead zones, which can not be controlled by a PID controller. In this paper, the friction characteristics of a cylinder is examined, which may cause the abrupt increase of the acceleration in the zero-crossing speed region. To overcome the drawbacks of a PID controlled hydraulic system, a zooming fuzzy logic controller is designed and finally an improved hybrid controller is Proposed. The proposed controller is composed of the PID controller and the zooming fuzzy controller. The effectiveness of the proposed control scheme is shown by simulation and experimental results, In which the proposed hybrid control method yields good control performance not only in the zero-crossing speed region but also In the overall control region including steady-state region.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.768-773
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• 2003

Injection molding has been widely used for the mass production of a plastic product. With the development of the relative technique, various injection molding techniques have been developed and we could get more precise plastic product. The temperature of a melting resin is an important factor in the injection molding and this temperature has direct influence on the quality of a plastic product. In the present injection molding machine, the deriation of a temperature controlled by PID control method is within 2$^{\circ}C$ in the injection molding machine but PID control method takes too much time to stabilize after preheating and its overshoot is so big. We applied fuzzy control to alleriate the problem. In this research, we experimented the fuzzy temperature control with the usage of PC based PLC.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.10
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• pp.1287-1296
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• 2014

This paper is about control of Automated Guided Vehicle for path following using fuzzy logic controller. The Automated Guided Vehicle is a tricycle wheeled mobile robot with three wheels, two fixed passive wheels and one steering driving wheel. First, kinematic and dynamic modeling for Automated Guided Vehicle is presented. Second, a controller that integrates two control loops, kinematic control loop and dynamic control loop, is designed for Automated Guided Vehicle to follow an unknown path. The kinematic control loop based on Fuzzy logic framework and the dynamic control loop based on two PID controllers are proposed. Simulation and experimental results are presented to show the effectiveness of the proposed controllers.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.496-500
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• 1993

This paper presents an end-point position control of 1-link flexible robot arm by the PID self-tuning fuzzy algorithm. The governing equation is derived by the extended Hamilton's principle and based on the Bernoullie-Euler beam theory. The governing equation is solved by applying the Laplace transform and the numerical inversion method. The arm is mounted on the translational mechanism driven by a ballscrew whose rotation is controlled by dcservomotor. Tip position is controlled by the PID self-tuning fuzzy algorithm so that it follows a desired position. This paper shows the experimental and theoretical results of tip dispalcement, and also shows the good effects reducing the residual vibration of the end-point.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.71-71
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• 2000

In this paper, the fuzzy system is applied to MCZ Crystal Grower using at industrial field. The existing controller, which is PID controller, has a fixed gain and as a result of it it can not have an adaptive control function against the error or disturbance. Hence, the machine operator should always check the process status and when the error is occurred, the quality and the productivity may be decreased by each personal capability. In order to remove this drawback, a fuzzy control system which is known to be adaptive and flexible is applied to the machine. After applying the fuzzy system, and compared with the existing system, the diameter deviation and the defects were decreased. we proved the possibility of application fuzzy system to single silicon crystal grower.

• Journal of the Semiconductor & Display Technology
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• v.6 no.4
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• pp.17-22
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• 2007

Vibration isolation equipments are mostly required in precise measurement and manufacturing system. Among all the vibration isolation equipments, air-spring is the most widely used equipment because of low resonant frequency and high damping ratio. In this study, we used Takagi-Sugeno fuzzy method to design an active vibration isolation system using air-spring, and compared the fuzzy method with passive control method and PID control method. Due to the non-linearity characteristics of air-spring, fuzzy controller was verified to be the most effective both in simulation and experiment.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.539-542
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• 2005

This paper contains studies which are Cruise speed control which is made by PID algorithm and automated steering system for avoiding the obstacle coming from the front which is using Fuzzy algorithm. This mobile car uses DC motor whose speed is detected by encoder. Ultrasonic Waves Sensor established in the front detects the obstacle and the curve. And the sensor established in the side detects the distance of the space of the road. If the sensor detects the obstacle or the curve, the car is controlled by using Fuzzy algorithm. The Fuzzy algorithm calculates the speed and steering angle by using the value which is obtained from sensor.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.279-284
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• 2014

This paper proposes a optimum design method for the Fuzzy PID controller of magnetic levitation-based Rail-Guided Vehicle(RGV). Since an attraction type levitation system is intrinsically unstable, it is difficult to completely satisfy the desired performance through the methods designed by conventional controllers. In the paper, the Fuzzy PID controller with fixed parameters are applied and then the optimum parameters of fuzzy PID controller are selected by genetic algorithm. For the fitness function of genetic algorithm, the performance index of PID controller is used. To verify the performance of the proposed method, we used Matlab/simulink model of Maglev and compared the proposed method with the performance of PID controller. The simulation results show that the proposed method is more effective than conventional PID controller.