• Journal of Electrical Engineering and Technology
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• v.4 no.1
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• pp.66-78
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• 2009

This paper introduces the design of a fuzzy logic controller in conjunction with direct torque control strategy for a Permanent Magnet synchronous machine. A stator flux angle mapping technique is proposed to reduce significantly the size of the rule base to a great extent so that the fuzzy reasoning speed increases. Also, a fuzzy resistance estimator is developed to estimate the change in the stator resistance. The change in the steady state value of stator current for a constant torque and flux reference is used to change the value of stator resistance used by the controller to match the machine resistance.

• Journal of Biosystems Engineering
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• v.21 no.2
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• pp.167-174
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• 1996

A Fuzzy Logic Controller(FLC) was developed for the autonomous operation of speedsprayer in an orchard. The autonomous operation with the FLC was graphically simulated under the real condition of the orchard. Image processing was used to find out the direction of running and four ultrasonic sensors were used to detect obstacles for the running. The simulation results showed that the speedsprayer could be operated autonomously with the FLC combined with the image processing and the ultrasonic sensors.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1114-1115
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• 2007

In this paper, a new speed sensorless control based on a fuzzy compensator are proposed for the interior permanent magnet synchronous motor (IPMSM) drives. The conventional proportional plus integrate(PI) control are very sensitive to step change of the command speed, parameter variations and load disturbance. To cope with these problems of the PI control, the estimated speeds are compensated by using the fuzzy logic controller (FLC). In the FLC used by the speed compensator of the IPMSM, the system control parameters are adjusted by the fuzzy rule based system, which is a logical model of the human behavior for process control. The effectiveness of algorithm is confirmed by the experiments.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1172-1174
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• 2002

An adaptive fuzzy P + ID controller for variable speed operation of BLDC motor drives is presented in this paper. Generally, a conventional PID controller is most widely used in industry due to its simple control structure and ease of design. However, the PID controller suffers from the electrical machine parameter variations and disturbances. To improve the tracking performance for parameter and load variations, the controller proposed in this paper is constructed by using an adaptive fuzzy logic controller in place of the proportional term in a conventional PID controller. For implementing this controller, only one additional parameter has to be adjusted in comparison with the PID controller. An adaptive fuzzy controller applied to proportional term to achieve robustness against parameter variations has simple structure and computational simplicity. The controller based on optimal fuzzy logic controller has an self-tuning characteristics with clustering. Computer simulation results show the usefulness of the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.44-47
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• 1996

Bang-bang control law provides the optimal solution for a minimum-time control problem, but ignores the intermediate path except for the initial and final points. In this paper, a near minimum-time suboptimal fuzzy logic controller is introduced that can control the intermediate path. A dynamic model for a system is established using the average dynamics method of linearization. System model is continuously updated over the control time periods. This makes it suitable for high speed or variable payload applications. Bang-bang control theory is modified and used to derive the preliminary control law. A fuzzy logic algorithm is then applied to adjust and find the best solution. The solution will provide the suboptimal minimum-time control law which can avoid obstacles in the workspace.

• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.1
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• pp.111-119
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• 2013

This paper present stabilization control of fixed speed wind generator by using variable speed permanent magnet wind generator in a wind farm connected with multi-machine power system. A novel direct-current based d-q vector control technique of back to back converter integrated with Fuzzy Logic Controller for optimal control configuration is proposed, in which both active and reactive powers delivered to a power grid system are controlled effectively. Simulation analyses have been performed using PSCAD/EMTDC. Simulation results show that the proposed control scheme is very effective to enhance the voltage stability of the wind farm during fault condition.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.131-134
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• 1997

This paper presents a new approach to the design of intelligent control system for track vehicle system using fuzzy logic based on neural network. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is illustrated by simulation for trajectory tracking of track vehicle speed.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.8
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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.

• Textile Coloration and Finishing
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• v.15 no.4
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• pp.39-42
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• 2003

Automatic concentration control system for pretreatment of dyeing was set up with adaptive control system supported by Fuzzy logic for the high speed successive pretreatment of fabric. Concentration of pretreatment bath was determined by the conductivity due to the ionized NaOH. Usability of this system was also evaluated with 30wt% of NaOH (conductivity of 0.25 S/cm) as an initial concentration. Conductivity fluctuated between 0.31 and 0.17 S/cm. This range accorded with the 21-35wt% of NaOH concentration.

• Proceedings of the KIEE Conference
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• 2001.07e
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• pp.58-61
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• 2001

The purpose of this paper is a fuzzy logic controller for XY positioning system. The overall control system consists of three parts, the position controller, the speed controller, the fuzzy logic controller. Precise tracking is achieved by fuzzy logic controller. In practice, such systems contain many uncertainties. Therefore, the XY positioning system must receive and evaluate the motion of all axis 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. So, we propose a fuzzy logic controller of XY positioning system. Experimental results show that the proposed fuzzy logic controller is effective to improve the contouring accuracy of XY positioning system.