• Journal of the Korean Society for Precision Engineering
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• v.20 no.6
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• pp.55-61
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• 2003

Control of multi-link robot arms is a challenging and difficult problem because of the highly nonlinear dynamics. Independent joint adaptive scheme is developed for control of robot manipulators based on Sugeno-type of fuzzy logic. Fuzzy logic system is used to approximate the coupling forces among the joints, coriolis force, centrifugal force, gravitational force, and frictional forces. The proposed scheme does not require an accurate manipulator dynamic, and it is proved that closed-loop system is asymptotic stable despite the gross robot parameter variations. Numerical simulations for three-axis PUMA robot are included to show the effectiveness of controller.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1658-1661
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• 2002

In this paper, we propose the intelligent inference trace algorithm of the mobile robot using fuzzy logic. With the proposed algorithm, the mobile robot can trace human at regular intervals. The mobile robot can recognize the distances between it and human with both multi-ultrasonic sensors and PC-camera and then, can inference the direction and velocity of itself to keep the given regular distances. In the first, the mobile robot acquires the information about circumstances using ultrasonic sensor and PC-camera then secondly, recognize the status of circumstances using the fuzzy logic. We also evaluate the experimental navigation test at several times to verify the ability of the fuzzy logic controller.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2398-2400
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• 2000

In this paper, we consider multi-objective synthesis of fuzzy controllers for a widely used special class of the Takagi-Sugeno(TS) fuzzy systems. We propose a new fuzzy controller utilizing the strategy of rescaling and show that synthesis of the proposed controllers satisfying multiple design objectives can be reduced to a simple linear matrix inequality(LMI) problem. Finally, an application to an inverted pendulum on a cart is presented to illustrate the validity of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.694-697
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• 1996

The aim of this work for 5 years from 1994 is to develop a multi-fingered robot hand and its control system for grasp and manipulation of objects dexterously. Since the robot hand is still being developed, a commercialized robot hand from Barrett Company is utilized to implement a hand controller and control algorithm. For this, VME based motion control and interface boards are developed and multi-sensors such as encoder, force/torque sensor, dynamic sensor and artificial skin sensor are partly developed and employed for the grasping control algorithm. In oder to handle uncertainties such as mechanical idleness and backlash, a fuzzy rule based grasping algorithm is also considered and tested with the developed control system.

• Proceedings of the KIEE Conference
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• 1992.07b
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• pp.1228-1230
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• 1992

The permanent magnet synchronous motor(PMSM) is receiving Increased attention for servo drive applications in recent years because of its high torque to inertia ratio, superior power density and high efficiency. By vector-controll method, PMSM has the same operating characterics as seperately excited dc motor. The drive system of servo motor is requested to have an accurate response for the reference input and a quick recovery for the disturbance such as load torque. However, when the unknown disturbances and parameter variations are imposed on the permanent magnet synchronous motor(PMSM), the drive system is significantly effected by them. As a result, the drive system with both a fast compensation and a robustness to a parameter variations is requested. This paper investigates the possibility of applying the fuzzy logic controller(FLC) using Multi-Rule Base In a servo motor control system. In this paper, The five Rule Bases(1 to 5) are selected to recover the state error caused by the disturbance in steady state. In the initial operating mode. Rule Base 0 is used. To show the validity of the proposed fuzzy logic controll system, the computer simulation results are provided.

• 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 the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.9
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• pp.26-35
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• 2010

The maximum output torque developed by the machine is dependent on the allowable current rating and maximum voltage that the inverter can supply to the machine. Therefore, to use the inverter capacity fully, it is desirable to use the control scheme considering the voltage and current limit condition, which can yield the maximum torque per ampere over the entire speed range. This controller is controlled speed and current using hybrid PI(HBPI) controller and estimation of speed using ANN. Also, this paper is proposed maximum torque control of induction motor using slip angular speed and current condition at widely speed range. The performance of the proposed induction motor drive with maximum torque control using HBPI controller is verified by analysis results at dynamic operation conditions.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.2
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• pp.9-15
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• 2001

This paper describes a new method of Genetic Algorithms for Adaptive Fuzzy Control System. Previous works using a Multi-population Genetic Algorithm have divided chromosome into two components, rule sets and membership functions. However, in this case bad rule sets disturb optimization in good rule sets and membership functions. A new method for a Multi population Genetic Algorithm suggests three components, good rule sets, bad rule sets, and membership functions. To show the effectiveness of this method, fuzzy controller is applied to a Truck Backing Problem. Results of the computer simulation show good adaptation of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.866-871
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• 1991

The multi-layer neural network possesses the desirable characteristics of parallel distributed processing and learning capacity, by which the uncertain variation of the parameters in the dynamically complex system can be handled adoptively. However the error back propagation algorithm that has been utilized popularly in the learning procedure of the mulfi-Jayer neural network has the significant limitations in the real application because of its slow convergence speed. In this paper, an approach to improve the convergence speed is proposed using the fuzzy logic that can effectively handle the uncertain and fuzzy informations by linguistic level. The effectiveness of the proposed algorithm is demonstrated by computer simulation of PUMA 560 robot manipulator.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.8
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• pp.165-173
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• 1998

In this paper, a motion control algorithm is developed by using fuzzy control technique, which makes a robot arm avoid unexpected obstacles when the robot is moving from the start to a goal posture. During the motion, if there exist no obstacles the robot arm moves along the pre-defined path. But if some obstacles are recognized and close to the robot arm, a fuzzy controller is activated to adjust the path of the robot arm. To show the feasibility of the developed algorithm, numerical simulations and experiments are carried out. In the experiments, redundant planar robot arms are considered for the collision avoidance test, and it was proved that the developed algorithm gives good collision avoiding performance.