• Transactions on Control, Automation and Systems Engineering
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• 제3권1호
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• pp.58-65
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• 2001

This paper proposes a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a robot. Using this method, the number of inference rules and the shape of membership functions are optimized without an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. And, it is guaranteed that he selected solution become the global optimal solution by optimizing the Akaikes information criterion expressing the quality of the inference rules. The trajectory tracking simulation and experiment of the polishing robot show that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the proposed fuzzy-sliding mode controller provides reliable tracking performance during the polishing process.

• 한국정밀공학회지
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• 제29권3호
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• pp.266-272
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• 2012

This paper has aims to share fundamental knowledge for magnetic abrasive polishing and to mainly introduce recent research results. In order to enhance a magnetic flux density for nonferrous materials, advanced magnetic abrasive polishing system which is called 2nd generation system was established by electro-magnet array table, and the effectiveness of the electromagnet array table was evaluated in real polishing experiments. To increase adhesiveness of the abrasives in high speed polishing, a silicone gel agent was proposed and carbon nanotube particles as new magnetic abrasives were applied in the magnetic abrasive polishing. In addition, a strategy for optimal step-over determination by heuristic algorithm was introduced for applying large size workpiece. Curved surfaces having a uniform radius were simulated and tested with installed electro-magnet array table.

• Journal of Mechanical Science and Technology
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• 제15권5호
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• pp.580-591
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• 2001

This paper proposes a fuzzy-sliding mode control which is designed by a self tuning fuzzy inference method based on a genetic algorithm. Using the method, the number of inference rules and the shape of the membership functions of the proposed fuzzy-sliding mode control are optimized without the aid of an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. It is further guaranteed that the selected solution becomes the global optimal solution by optimizing Akaikes information criterion expressing the quality of the inference rules. In order to evaluate the learning performance of the proposed fuzzy-sliding mode control based on a genetic algorithm, a trajectory tracking simulation of the polishing robot is carried out. Simulation results show that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the trajectory control result is similar to the result of the fuzzy-sliding mode control which is selected through trial error by an expert. Therefore, a designer who does not have expert knowledge of robot systems can design the fuzzy-sliding mode controller using the proposed self tuning fuzzy inference method based on the genetic algorithm.

• 디지털콘텐츠학회 논문지
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• 제3권1호
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• pp.113-122
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• 2002

반도체와 관련한 실리콘웨이퍼의 평탄도는 양질의 웨이퍼를 보증하는 가장 중요한 요소이다. 따라서 평탄도(flatness)를 측정하고 제어하는 Polishing이라는 공정은 웨이퍼 생산의 여러 라인중 특별히 중요시 되는 과정이며 현재 이 공정에서는 담당 엔지니어가 웨이퍼의 모형을 모니터에서 육안으로 관찰하여 판단하고 평탄도를 높이기 위한 제어를 하고 있다. 그러나 사람에 의한 것이므로 많은 경험이 필요하고 일일이 체크해야하는 번거로움이 있다. 본 연구는 이러한 비효율적인 작업의 효율화를 위해 이루어 졌으며 Polishing 공정에 있어 평탄도를 사람이 아닌 시스템에 의해 자동으로 측정하여 제어하는 알고리즘을 제안한다. 여기서 제안한 시스템은 보간 다항식을 이용하여 웨이퍼 전역의 두께를 추정하고 Polishing공정에서 평탄도를 높이기 위해 제어 가능한 모형별로 분류할 수 있도록 하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2010년도 추계학술대회 논문집
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• pp.137-138
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• 2010

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.173-176
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• 1999

This paper shows a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a Polishing robot. Using this method, the number of inference rules and the shape of membership functions are determined by the genetic algorithm. The fuzzy outputs of the consequent part are derived by the gradient descent method. Also, it is guaranteed that .the selected solution become the global optimal solution by optimizing the Akaike's information criterion expressing the quality of the inference rules. It is shown by simulations that the method of fuzzy inference by the genetic algorithm provides better learning capability than the trial and error method.

• 제어로봇시스템학회논문지
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• 제6권9호
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• pp.786-795
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• 2000

In this paper, a new impedance force control method for deburring and polishing process is proposed. The proposed method is robust to deal with unknown environment stiffness as unknown well as environment location. An adaptive technique is used to minimize the force error occurred due to unknown environment surface profile. A robust position control algorithm based on time-delayed information is used to cancel out uncertainties in robot dynamics. A three link robot manipulator is used to demonstrate performances of the proposed control on deburring and polishing tasks. Stability analysis for the adaptive control is presented and its results are confirmed by simulations.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.182-182
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• 2000

This paper proposes a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a robot. Using this method, the number of inference rules and the shape of membership functions are optimized without an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. And, it is guaranteed that the selected solution become the global optimal solution by optimizing the Akaike's information criterion. The trajectory trucking experiment of the polishing robot system shows that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the proposed fuzzy-sliding model controller provides reliable tracking performance during the polishing process.

• 한국생산제조학회지
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• 제20권2호
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• pp.174-179
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• 2011

This paper focuses on the optimal step-over value for magnetic tool path. Since magnetic flux density is changed according to distance from center of magnetic tool. Enhanced surface roughness is also different according to change of radius. Therefore, to get a identical surface roughness on workpiece, it is necessary to find optimal tool path including step-over. In this study, response surface models for surface roughness according to change of radiuses were developed, and then optimal enhanced surface roughness for each radius was selected using genetic algorithm and simulated annealing to investigate relation between radius and surface roughness. As a result, it found that step-over value of 6.6mm is suitable for MAP of magnesium alloy.

• 디지털콘텐츠학회 논문지
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• 제5권4호
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• pp.251-256
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• 2004

반도체 집적회로를 만드는 토대가 되는 실리콘 웨이퍼의 표면은 고품질 회로를 구성하기 위해 극도의 평탄도가 요구되므로 평탄도는 양질의 웨이퍼를 보증하는 가장 중요한 요소이다. 따라서 실리콘웨이퍼 생산의 10개의 공정 중 거칠어진 웨이퍼 표면을 고도의 평탄도를 갖도록 연마하는 폴리싱공정은 매우 중요시 되는 생산라인이다. 현재 이 공정에서는 담당 엔지니어가 웨이퍼의 모형을 측정장비의 모니터에서 육안으로 관찰하여 판단하고 평탄도를 높이기 위한 제어를 하고 있다. 그러나 사람에 의한 것이므로 많은 경험이 필요하고 일일이 체크해야하는 번거로움이 있다. 본 연구는 이러한 비효율적인 작업의 효율화를 위해 웨이퍼의 모형을 디지털 컨텐츠화하여 폴리싱 공정에 있어 평탄도를 사람이 아닌 시스템에 의해 자동으로 측정하여 제어하는 알고리즘을 제안한다. 또한 제안한 전체 웨이퍼 평탄도 추정알고리즘을 토대로 실제 현장에서 쓰이는 웨이퍼 각 사이트별 평탄도를 측정하기 위한 사이트두께 추정 알고리즘을 제안한다.