• Journal of Biosystems Engineering
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• v.25 no.1
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• pp.55-62
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• 2000

Autonomous farm operation needs to be developed for safety, labor shortage problem, health etc. In this research, an autonomous tractor for tillage was investigated using machine vision and a fuzzy logic controller(FLC). Tractor heading and offset were determined by image processing and a geomagnetic sensor. The FLC took the tractor heading and offset as inputs and generated the steering angle for tractor guidance as output. A color CCD camera was used fro the image processing . The heading and offset were obtained using Hough transform of the G-value color images. 15 fuzzy rules were used for inferencing the tractor steering angle. The tractor was tested in the file and it was proved that the tillage operation could be done autonomously within 20 cm deviation with the machine vision and the FLC.

• Journal of Biosystems Engineering
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• v.22 no.4
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• pp.487-496
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• 1997

A fuzzy logic controller(FLC) was developed for the autonomous travel of speedsprayer in an orchard. The autonomous travel with the FLC was graphically simulated under the conditions of an ordinary standard orchard. Differential global positioning system(DGPS) was used to find the direction of running and four ultrasonic sensors were used to detect obstacles during the running. The simulation results showed that the speedsprayer, by the FLC combined with DGPS and the ultrasonic sensors. could overcome the turning problem at comers which could not be solved with such a system as machine vision and might be operated autonomously.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.917-922
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• 2004

As the tasks of robots become more diverse, some complicated tasks have come to require force and position hybrid control. A compliant device can be used to control force and position simultaneously by separating the twist of the robot's end effector from the twist of compliance and freedom by using stiffness mapping of the compliant device. The development of a fuzzy gain scheduling scheme of control for a robot with a compliant device is described in this paper. Fuzzy rules and reasoning are performed on-line to determine the gain of twists based on wrench error and twist error and twist of compliance and twist of freedom ratio. Simulation results demonstrate that better control performance can be achieved in comparison with constant gain control.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.9
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• pp.108-115
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• 1997

This paper presents a robust controller design for uncertain nonlinear systems with input saturation. In actual application, the robust controller may require a high input torque so that it faces input saturation due to power limitation of the system. The satruation problem may cause instability of the system. To improve this problem, a robust controller using a fuzzy logic control is proposed. The proposed controller keeps state errors bounded. To validate the proposed controller, an invert pendulum and its control system is set up. The experimental result shows bounded angular position errors under saturated input torques.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.4
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• pp.51-60
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• 2011

Authentication model in the wireless environment has many security vulnerabilities. However, there is no adapting standard method in this field. Therefore, we propose a fuzzy logic based authentication model to enhance the security level in the authentication environment. We use fuzzy logic based classification to construct our model, and also additionally utilize improved AHP and case-based reasoning for an appropriate decision making. We compute the context information by using the improved AHP method, use the proposed model to compute the security level for the input data, and securely apply the proposed model to the wireless environment which has diverse context information. We look forward to better security model including cloud computing by extending the proposed method in the future.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.1
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• pp.10-18
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• 2000

This paper proposes a fuzzy logic cross-coupled controller using a new contouring modeling for a two-axis servo system. The general 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. The cross-coupled controller utilizes all axis position error information simultaneously to produce accurate contours. However, the conventional cross-coupled controllers cannot overcome friction, backlash, and parameter variations. Also since, it is difficult to obtain an accurate mathematical model of multi-axis system, here we investigate a fuzzy logic cross-coupled controller of servo system. In addition, new contouring error vector computation method is presented. The experimental results are presented to illustrate the performance of the proposed algorithm.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.4
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• pp.583-592
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• 1999

In order to control systems which contain nonlinearities control strategies must deal with the effects of them. Since most of control methods based on system mathematical models have been mainly developed focused on stability robustness against nonlinearities or uncertainties under the assumption that controlled systems are linear time invariant they have certain amount of limita-tions to smartly improve control perfomances of systems disturbed by nonlinearities or uncertainties. In this paper the fuzzy PID control law is suggested which can improve control performances of the nonlinear heavy load hydraulic systems disturbed by nonlinearities and uncertainties. Although the derivation process is based on the design process similar to general fuzzy logic con-troller resultant control law has analytical forms with time varying PID gains rather than linguis-tic forms so that implementation using commn-used versatile microprocessors can be achieved easily and effectively in real-time control aspect.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.10
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• pp.1905-1919
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• 2000

The main motivation of this research is to develop an intelligent control strategy for Activated Sludge Process (ASP). ASP is a complex and nonlinear dynamic system because of the characteristic of wastewater, the change in influent flow rate, weather conditions, and etc. The mathematical model of ASP also includes uncertainties which are ignored or not considered by process engineer or controller designer. The ASP is generally controlled by a PID controller that consists of fixed proportional, integral, and derivative gain values. The PID gains are adjusted by the expert who has much experience in the ASP. The ASP model based on $Matlab^{(R)}5.3/Simulink^{(R)}3.0$ is developed in this paper. The performance of the model is tested by IWA(International Water Association) and COST(European Cooperation in the field of Scientific and Technical Research) data that include steady-state results during 14 days. The advantage of the developed model is that the user can easily modify or change the controller by the help of the graphical user interface. The ASP model as a typical nonlinear system can be used to simulate and test the proposed controller for an educational purpose. Various control methods are applied to the ASP model and the control results are compared to apply the proposed intelligent control strategy to a real ASP. Three control methods are designed and tested: conventional PID controller, fuzzy logic control approach to modify setpoints, and fuzzy-PID control method. The proposed setpoints changer based on the fuzzy logic shows a better performance and robustness under disturbances. The objective function can be defined and included in the proposed control strategy to improve the effluent water quality and to reduce the operating cost in a real ASP.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.1
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• pp.35-47
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• 2004

In this paper presents a new approach to the design and real-time implementation of fuzzy control system based-on digital signal processors(DSP:IMS320C80) in order to improve the precision and robustness for system of industrial robot(Dual-Arm with 8 joint Robot). The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The IMS320C80 is used in implementing real time fuzzy control to provide an enhanced motion control for robot manipulators. In this paper, a Self-Organizing Fuzzy Controller(SOFC) for the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variables of the controller. In the synthesis of a FLC(Fuzzy Logic Controller), one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult SOFC is proposed for a hierarchical control structure consisting of basic and high levels that modify control rules. The proposed SOFC scheme is simple in structure, Int in computation, and suitable for implementation of real-time control. Performance of the SOFC is illustrated by simulation and experimental results for a Dual-Arm robot with eight joints.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.2
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• pp.223-231
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• 1997

A variety of approaches have been investigated for the application of spark-ignition engine knock control. The control method implemented, here as "Fuzzy Control", has the advantage of not requiring the knowledge of a mathematical model of the controlled object and is more robust and flexible than conventional approaches. Knock control in this study is performed using vibration signal which is measured with accelerometer attached to the cylinder block of a 1498cc four-cylinder spark-ignition engine. The experimental results obtained with this method are compared with those obtained with a knock interval controller and with those of a conventional controller. Those results illustrate better performance in torque than knock interval controller and conventional controller.ontroller.