• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.754-756
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• 2004

The ultrasonic piezo motor is a new type motor that has an excellent performance and many useful features that electromagnetic motors do not have. But, it suffers from severe system non-linearities and parameter variations especially during speed control. Therefore, it is difficult to accomplish satisfactory control performance by using the conventional PID controller. In this paper, to achieve the precise control, we analyzed response time & change with a driving time, and proposed PD controller combined with neural network. The backpropagation algorithm is used to train a given trajectory. The effectiveness of the used method is confirmed by experiments. The effectiveness of the used method is confirmed by experiments using the ultrasonic motor made in Korea.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.1
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• pp.10-15
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• 2004

We present a state-space approach to make non-square linear systems strictly passive by using an input-dimensional parallel feedforward compensator. A necessary and sufficient condition for the existence of the parallel feedforward compensator is given by the static output feedback formulation, which enables to utilize linear matrix inequality. By modifying the structure of the compensator the additional technical assumption in the previous result [1] is removed. The effectiveness of the proposed method is illustrated by some numerical examples which can be stabilized by the proportional-derivative (PD) and proportional-derivative-integral (PID) control laws. The proposed control scheme can successfully replace the measurements of derivative terms in the control laws.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.732-735
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• 2007

Recently the control of induction motor for position control has been extensively studied. The representative method is PIDA controller proposed by Jung&Dorf. By designed PIDA controller' parameter had large value. Moreover, this method is very analyze, so that, not adapted controller parameter in disturbance. Besides using generalize fuzzy controller. Because input and output membership function is linguistic type, therefore system response is very slow. So, in this paper we used optimized fuzzy controller. Optimized fuzzy controller is output membership function is unity value. The controller performance was estimated applied to induction motor' position control.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.671-676
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• 2007

In this paper, a novel neuro-fuzzy controller is presented. The generic fuzzy controller is compensated by a neural network controller so that an overall control structure forms a neuro-fuzzy controller. The proposed neuro-fuzzy controller solves the difficulty of selecting optimal fuzzy rules by providing the similar effect of modifying fuzzy rules simply by changing crisp input values. The performance of the proposed controller is tested by controlling humanoid robot arms. The humanoid robot arm is analyzed and implemented. Experimental studies have shown that the performance of the proposed controller is better than that of a PID controller and of a generic fuzzy PD controller.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2089-2092
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• 2002

The PID controller have the simple structure and show the comparatively good control performance. Crystal Grower(FF-CZ150) melt polycrystalline silicon at the temperature of about 1450$^{\circ}C$, then grow it into a single crystalline ingot. The automatic diameter control system of the Crystal Grower has a good performance with only PD control. But it contain the integrator in the plant which has a long time delay. In this paper, we show the secondary approximate model and applies time delay controller which has good performance for the plant with long time delay. It will be able to improve the response characteristic against a standard input and a load disturbance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.2
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• pp.165-171
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• 2005

The ultrasonic piezo motor is a new type motor that has an excellent performance and many useful features that electromagnetic motors do not have. But, it suffers from severe system non-linearities and parameter variations especially during speed control. Therefore, it is difficult to accomplish satisfactory control performance by using the conventional PID controller. In this paper, to achieve the precise control for linear type ultrasonic motor was analyzed as a function of response time and change with a driving time. Also, we propose controller that combines STEP controller and PD controller that have error of ${\mu}m$ about liner type ultrasonic motor.

• Nuclear Engineering and Technology
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• v.25 no.2
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• pp.222-232
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• 1993

In this paper, we present two sets of fuzzy algorithms for the steam generator level control ; one for the high power operations where the flow error is available and the other for the low power operations where the flow error is not available. These are converted to a PID type controller for the high power case and to a quadratic function form of a controller for the low power case. These controllers are implemented on the Compact Nuclear Simulator at Korea Atomic Energy Research Institute and tested by a set of four simulation experiments for each. For both cases, the results show that the total variation of the level error and of the flow error are about 50% of those by the PI controllers with about one half of the control action. For the high power case, this is mainly due to the fact that a combination of two PD type controllers in the velocity algorithm form rather than a combination of two PI type controllers in the position algorithm form is used. For the low power case, the controller is essentially a PID type with a very small integral component where the average values for the derivative component input and for the controller output are used.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2240-2245
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• 2003

In this paper, the controller design by coefficient diagram method (CDM) for controlling the trolley position, load-swing angle and hoisting rope length of the overhead crane system simultaneously is proposed. The overhead crane system is a MIMO system consisting of two inputs and three outputs. Its mathematical model is nonlinear with coupling characteristics. This nonlinear model can be approximated to obtain a linear model where the first input mainly affects the trolley position and the load-swing angle while the second input mainly affects the hoisting rope length. In order to utilize the CDM concept for assigning the controllers, namely PID, PD and PI controllers separately, the model is approximated to be three transfer functions in accordance with trolley position, the load-swing angle and the hoisting rope length controls respectively. The satisfied performances of the overhead crane system controlled by the these controllers and fast rejection of the disturbance effect occurred at the trolley position are shown by simulation and experimental results.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.2
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• pp.30-38
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• 2003

This paper proposed PID controller for torch slider and PD controller for motor right wheel. to control the motion of two-wheeled welding mobile robot with seam tracking sensor touched on welding line. The motion control is realized in the view of keeping constant welding velocity and precise seam tracking even though the target welding line is on straight line or curved line. The position and direction of the body of the mottle robot are controlled by using signal errors between seam tracking sensor and body positioning sensor attached on the end of torch slider and body side of the mobile robot, respectively. In turning motion, the body and the torch slider are controlled by using the kinematic model related with two motions of body turning and torch sliding. The straight locomotion is controlled according to eleven control patterns obtained from displacements between two sensors of the seam tracking sensor and the body positioning sensor. The effectiveness is proven through the experimental results fur lattice type welding line. Through the experimental results, we can see that the position value of the electrode end point and the welding velocity are controlled almost constantly both in straight and turning locomotion.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.8
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• pp.352-359
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• 2002

A neuro-fuzzy controller has some problems that he difficulty of tuning up the membership function and fuzzy rules, long time of inferencing and defuzzifying compare to PID. Also, the fuzzy controller's own defect as a PD controller has. In this study, it is proposed two methods to solve these problems. The first method is that inner fuzzy rules are tuned up automatically by the back propagation learning according to error patterns. And the second method is a new type defuzzification method that shorten the calculation time of an inferencing and a defuzzifying. In this study, it is designed the new type neuro-fuzzy controller that improves the fast response and the stability of a system by using the proposed methods. And, the designed controller is named EPLNFC(Error pattern Learning Neuro-Fuzzy Controller). To evaluate the fast response and the stability of EPLNFC designed in this study, EPLNFC is applied to a speed control of a DC motor and AC motor.