• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.104-111
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• 2000

A fuzzy logic Run-by-Run(RbR) controller and an in -line wafer characteristics prediction scheme for the rapid thermal processing system have been developed for the study of process repeatability. The fuzzy logic RbR controller provides a framework for controlling a process which is subject to disturbances such as shifts and drifts as a normal part of its operation. The fuzzy logic RbR controller combines the advantages of both fuzzy logic and feedback control. It has two components : fuzzy logic diagnostic system and model modification system. At first, a neural network model is constructed with the I/O data collected during the designed experiments. The wafer state after each run is assessed by the fuzzy logic diagnostic system with featuring step. The model modification system updates the existing neural network process model in case of process shift or drift, and then select a new recipe based on the updated model using genetic algorithm. After this procedure, wafer characteristics are predicted from the in-line wafer characteristics prediction model with principal component analysis. The fuzzy logic RbR controller has been applied to the control of Titanium SALICIDE process. After completing all of the above, it follows that: 1) the fuzzy logic RbR controller can compensate the process draft, and 2) the in-line wafer characteristics prediction scheme can reduce the measurement cost and time.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.601-604
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• 1996

It is well known that steam generator water level control at low power operation has many difficulties in a PWR (pressurized water reactor) nuclear power plant. The reverse process responses known as shrink and swell effects make it difficult to control the steam generator water level at low power. A new automatic control logic to remove the reverse process responses is proposed in this paper. It is implemented in PLC (programmable logic controller) and evaluated by using test equipment in Korea Atomic Energy Research Institute. The simulation test shows that the performance requirements is met at low power (below 15%). The water level control by new control logic is stabilized within 1% fluctuation from setpoint, while the water level by YGN 3 and 4 control logic is unstable with the periodic fluctuation of 25% magnitude at 5% power.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1950-1955
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• 1991

A fuzzy dynamic learning controller is proposed and applied to control of time delayed, non-linear and unstable chemical processes. The proposed fuzzy dynamic learning controller can self-adjust its fuzzy control rules using the external dynamic information from the process during on-line control and it can create th,, new fuzzy control rules autonomously using its learning capability from past control trends. The proposed controller shows better performance than the conventional fuzzy logic controller and the fuzzy self organizing controller.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.1
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• pp.59-66
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• 2000

As the highly complex and precise control functions are required in modern industrial process control system, the complex function models and developed in each hardware and software of PLC. The SFC graphical language is very powerful for describing the sequential logic control algorithm, on the other hand it graphical language is very powerful for describing the sequential logic control algorithm, on the other hand it has problems in describing the interlock logic control algorithm, such as error management algorithm. In this paper, we propose the efficient error management method using the action qualifiers to design the error management algorithm in industrial process control system described scheme, we realize the error management logic in process control system of film coating machine.From the experiment results, we confirm that the proposed scheme is very useful in aspects to realize easily th error management logic and to reduce the memory capacity for user's program.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.2
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• pp.126-131
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• 2015

Studies on the control of inverted pendulum type systems have been widely reported. This is because this type of system is a typical complex nonlinear system and may be a good model to verify the performance of a proposed control system. In this paper, we propose the design of two fuzzy logic control systems for the control of a Segway mobile robot which is an inverted pendulum type system. We first introduce a dynamic model of the Segway mobile robot and then analyze the system. We then propose the design of the fuzzy logic control system, which shows good performance for the control of any nonlinear system. In this paper, we here design two fuzzy logic control systems for the position and balance control of the Segway mobile robot. We demonstrate their usefulness through simulation examples. We also note the possibility of simplifying the design process and reducing the computational complexity. This possibility is the result of the skew symmetric property of the fuzzy rule tables of the system.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.452-457
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• 1999

The recent control system has been changed into the type of PLC(Programmable Logic Controller) control. Up to now, systematic approach of PLC programming or control logic design is not suggested. In this study, the design process of the control logic is systematized and concrete process in each step is suggested. This systematized approach lead developer to be convenient to implement control system. When some error is occurred in the system, this approach enable the developer to analyze the reason of error rapidly and the system is amended according to systematic information of the analysis. The example of control system implementation following this approach is introduced.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.780-785
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• 1992

We present a multi-sensor fusion method in positioning control of a robot by using fuzzy logic. In general, the vision sensor is used in the gross motion control and the force/torque sensor is used in the fine motion control. We construct a fuzzy logic controller to combine the vision sensor data and the force/torque sensor data. Also, we apply the fuzzy logic controller to the peg-in-hole process. Simulation results uphold the theoretical results.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.493-495
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• 1998

Robust design is one method to make manufacturing less sensitive to manufacturing process. Also it is cost effective technique to improve the quality process. This method uses statistically planned experiments to vary settings of important process control parameters. In this paper we apply fuzzy optimization and fuzzy logic system to robust design concept. First a method which uses fuzzy optimization in obtaining optimum settings by measured data from experiments will be presented. Second, fuzzy logic system is made to reduce experiments using experiments results consisted with key control parameter combinations. Then optimum parameter set points are obtained by the descrebed first fuzzy optimization method after prediction the results of each parameter combinations considering each control parameter variations by nonsingleton fuzzy logic system concept.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1687-1692
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• 1991

Burrs, created when metals deform plastically, are by-products of most machining processes. The increasing requirements of precision and reliability in manufacturing processes have led to the development of systems for automated deburring. In this paper the motivations and requirements for automated robotic deburring are discussed. Also, the feasibility of automating the deburring process using fuzzy logic controller is investigated. In implementing the fuzzy logic controller, particular attention is paid to the acoustic emission sensing for the characterization and feedback control of the burr removal process. The results of the experiments reveal the rule based control scheme based on fuzzy logics can be a good alternative to traditional control schemes.

• ETRI Journal
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• v.41 no.3
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• pp.383-395
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• 2019

Clock Controlled Dual keeper Domino logic structures (CCDD_1 and CCDD_2) for achieving a high-speed performance with low power consumption and a good noise margin are proposed in this paper. The keeper control circuit comprises an additional PMOS keeper transistor controlled by the clock and foot node voltage. This control mechanism offers abrupt conditional control of the keeper circuit and reduces the contention current, leading to high-speed performance. The keeper transistor arrangement also reduces the loop gain associated with the feedback circuitry. Hence, the circuits offer less delay variability. The design and simulation of various wide fan-in designs using 180 nm CMOS technology validates the proposed CCDD_1 and CCDD_2 designs, offering an increased speed performance of 7.2% and 8.5%, respectively, over a conventional domino logic structure. The noise gain margin analysis proves good robustness of the CCDD structures when compared with a conventional domino logic circuit configuration. A Monte Carlo simulation for 2,000 runs under statistical process variations demonstrates that the proposed CCDD circuits offer a significantly reduced delay variability factor.