• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.409-412
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• 1998

In this paper, we present an $H^2$ controller design of RTP(rapid thermal processing) systems satisfying robust stability and performance using weighted mixed sensitivity minimization. In industrial fields, RTP system is widely used for improving the oxidation and the annealing in semiconductor manufacturing process. The main control factors are temperature control of wafer and uniformity has been solved by PID control method. Because the reference inputs of RTP are ramp, we improve performance of RTP system by the design of $H^2controller$ using the weighted mixed sensitivity function. Also we compare $H^2controller$ with PID controller in terms of performance. An example is proposed to show the validity of proposed method.

• Journal of the Korea Convergence Society
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• v.4 no.2
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• pp.43-50
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• 2013

Sliding mode control(SMC) are carried out in this literature. And to make the controllers perform better, fuzzy logic was chosen,it makes PID controller auto-tuning parameters and reduced the chattering problem of sliding mode control. Since SMC take error and derivative of error as inputs, after comparison some results are obtained.PID controller response faster yet sliding mode control is much steadier. However certain problems cannot be ignored that the chattering phenomenal cannot be reduced entirely and this motion may hurt the machine; this project only considered a simple system, there is no guarantee PID can work as well as in this case for a much more complex system. MATLAB simulink was the main approach to obtain the performance of the two controllers: to observe the control output of the two controllers, electric circuit and special controllers are designed and tested in MATLAB.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.68-74
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• 2008

In this paper, a novel neural fuzzy control method is proposed to control nonlinear systems. A standard PD-like fuzzy controller is designed and used as a main controller for the system. Then a neural network controller is added to the reference trajectories to form a neural-fuzzy control structure and used to compensate for nonlinear effects. Two neural-fuzzy control schemes based on two well-known neural network control schemes, the feedback error learning scheme and the reference compensation technique scheme as well as the standard PD-like fuzzy control are studied. Those schemes are tested to control the angle and the position of the inverted pendulum and their performances are compared.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.318-319
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• 2008

In this paper, a steering feel simulator is designed and implemented using a steering wheel with a rotation angle sensor, torque sensor, and an ac motor for the generation of the required torque. The controller in the simulator consists of a 16-bit micro-controller, a D/A converter and A/D converters. The main objective of the controller is to perform torque control where the reference torque is calculated from the torque map for both the vehicle velocity and the wheel sensor cutout. It is shown via the experimentation using the proposed simulator that the simulator output performance can be easily understood for the variation of vehicle parameters or controller parameters.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.236-238
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• 2005

In this paper, we propose a new discrete-time predictive current controller for a PMLSM(permanent magnet linear synchronous motor). The main objectives of the current controllers are that the measured stator current is tracked the command current value accurately and the transient interval is shorten as much as possible, in order to obtain high-performance of ac drive system. The conventional predictive current controller is hard to implement in full digital current controller since a finite calculation time causes a delay between the current sensing time and the time that take to apply the voltage to motor. A new control strategy is the schema that gets the fast adaptation of transient current change, the fast transient response tracking. Moreover, the simulation results will be verified the improvements of Predictive controller and accuracy of the current controller.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2552-2556
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• 2005

In general, the forklift driven by DC motor drive system is used in the industrial field. Classically, the DC motor is controlled by current control using proportion control method, by output torque following the load on the plane like a manual operation. But in the industrial field, the forklift is demanded the robust drive mode. Some cases of the mode, there aretrouble in torque control following slope capacity. The control is sensitive concerning about slope angle and output speed, various control method is studied for stability of speed control. In this paper, I apply current control for the self-tuning using the fuzzy controller to obtain robust, stable speed control and use stable, high efficiency control using DSP as main controller for high speed processor, embody dynamic characteristic of control compared the PI controller to the fuzzy controller.

• Proceedings of the KIEE Conference
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• 1999.07f
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• pp.2801-2803
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• 1999

An unified controller for emergency generator is presented to control AVR and Governor and l00kVA power conditioner. This controller is operated to compensate current harmonics and asymmetries caused by nonlinear load and unbalance loads. The power conditioner shapes the source current sinusoidal in phase with source voltage and allows the generator to maximum power even to the single phase load. Also this power conditioner allows that three phase generator synchronizes with single phase main source and load sharing. An l00kVA generator system was built and the unified controller is realized with DSP(TMS320C32PCMA). Experimental results for many load conditions are presented to verify the performance of the unified controller.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.65-69
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• 2002

The main drawback of “classical”fuzzy systems is the inability to design and maintain their database. To overcome this disadvantage many types of extensions adding the adaptivity property to those systems were designed. This paper deals with one of them a new hybrid adaptation structure, called gradient-incremental adaptive fuzzy controller connecting gradient-descent methods with the so-called self-organizing fuzzy logic controller designed by Procyk and Mamdani. The aim is to incorporate the advantages of both Principles. This controller was implemented and tested on the system of LEGO robots. The results and comparison to a ‘classical’(non-adaptive) fuzzy controller designed by a human operator are also shown here.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.75.5-75
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• 2001

In this paper, we study design of a ILQ(Inverse Linear Quadratic optimal control) looper control system for hot strip mills. The looper which is placed between stands plays an important role in controlling strip width by regulating strip tension variation generated from the velocity difference of main work rolls. A Looper servo controller is designed by ILQ control theory which is an inverse problem of LQ(Linear Quadratic optimal control) control. The mathematical model for looper system is obtained by Taylor´s linearization of nonlinear differential equations. Then we designed linear controller for linearization model by using the ILQ control algorithm. Thereafter this controller is applied to the nonlinear model for model identification. As a result, we show the controller´s robustness for the model error, external disturbance and sensor noise.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.9
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• pp.861-869
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• 2012

This paper presents a high performance position controller in a driving system using a time optimal control which is widely used to control driving systems to a desired reference position or velocity in minimum response time. The main purpose of this study is an improvement of transient response performance rather than steady-state response comparing with another various control strategies. In order to improve the performance of time optimal control, we tried to find the cause of the steady-state error in the driving system we have already made up and also suggest the newly modified type of time optimal control method in this paper.