• Journal of Institute of Control, Robotics and Systems
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• v.2 no.1
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• pp.60-66
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• 1996

Model Based Predictive Control(MBPC) has been widely used in predictive control since 80's. GPC[1] which is the superset of many MBPC strategies a popular method, but GPC has some weakness, such as insufficient stability analysis, non-applicability to internally unstable systems. However, CRHPC[2] proposed in 1991 overcomes the above limitations. So we chose RHPC based on CRHPC for electric furnace control. An electric furnace which has nonlinear properties and large time delay is difficult to control by linear controller because it needs nearly perfect modelling and optimal gain in case of PID. As a result, those controls are very time-consuming. In this paper, we applied RHPC with equality constraint to electric furnace. The reults of experiments also include the case of RHPC with monotonic weighting improving the transient response and including unmodelled dynamics. So, This paper proved the practical aspect of RHPC for real processes.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.149-155
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• 1997

본 논문에서는 비선형 시변 시스템을 제어할 경우 제어시스템의 안정성을 보장하고 성능을 향상시키기 위한 새로운 적응제어 구조를 전개하였다. 주어진 플랜트가 선형 시불변이라는 가정하에 표준 기준 모델 적응제어기가 적용될 경우 발생되는 출력오차는 플랜트의 비선형 시변특성으로 인하여 점근적으로 0에 수렴되지 않는다. 이때 미지의 출력오차를 점근적으로 0에 수렴시키는 방법으로 퍼지보상기를 사용하였으며 결과적으로 플랜트의 비선형 시변 특성을 보상하는 효과를 얻을 수 있었다. 퍼지 보상기로는 출력오차등의 조건에 따라 이득이 변하는 퍼지 PID 보상기를 도입하여 안정하게 설계되도록 노력하였다. 또한 출력오차를 점근적으로 0에 수렴시키는 것은 표준 기준 모델 적응제어기 내부의 모든 파라미터와 신호가 유한하게 됨을 의미하기 때문에, 제어시스템 전체의 안정도를 보장할 뿐만 아니라 결과적으로 과도응답 성능을 향상시킬 수 있게 되었다. 몇가지 예제를 대상으로 시뮬레이션을 수행하고 그 결과를 분석함으로써 비선형 시변 시스템을 제어할 경우 본 논문에서 전개된 새로운 적응제어 구조의 타당성을 확인하였다.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.33 no.4
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• pp.290-297
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• 1997

Underwater robotic vehicles(URVs) are used for various work assignments such as pipe-lining, inspection, data collection, drill support, hydrography mapping, construction, maintenance and repairing of undersea equipment, etc. As the use of such vehicles increases the development of vehicles having greater autonomy becomes highly desirable. The vehicle control system is one of the most critic vehicle subsystems to increase autonomy of the vehicle. The vehicle dynamics is nonlinear and time-varying. Hydrodynamic coefficients are often difficult to accurately estimate. It was also observed by experiments that the effect of electrically powered thruster dynamics on the vehicle become significant at low speed or stationkeeping. The conventional linear controller with fixed gains based on the simplified vehicle dynamics, such as PID, may not be able to handle these properties and result in poor performance. Therefore, it is desirable to have a control system with the capability of learning and adapting to the changes in the vehicle dynamics and operating parameters and providing desired performance. This paper presents an adaptive and learning control system which estimates a new set of parameters defined as combinations of unknown bounded constants of system parameter matrices, rather than system parameters. The control system is described with the proof of stability and the effect of unmodeled thruster dynamics on a single thruster vehicle system is also investigated.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.1
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• pp.80-88
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• 2010

In a conventional system, hydraulic unit pumps out pressurized oil when the power use is not even necessary. As a result, it causes much power loss. This study is on the proposal of new hydraulic unit which controls the revolution of the pump in order to produce proper power needed and to have good response characteristic. In addition, the existing control methods such as PID control method, fuzzy control method, and adaptive control method are applied to the proposed hydraulic unit. Then the best control method is selected and the controller is developed to realize minimum power loss.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.398-403
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• 2004

The demand of high speed machining is increasing because the high speed cutting providers high efficiency of process, short process time, improved metal removal capacity and better surface finish. Active magnetic bearings allow much high surface speed than conventional ball bearings and therefore greatly suitable for high speed cutting. The automatic control concept of magnetic bearing system provides ability of intelligent control of spindle system to increase accuracy and flexibility by means of adaptive vibration control. This paper describes a design and development of a milling spindle system which includes built-in motor with power 5.5㎾ and maximum speed 70,000rpm, HSK-32C tool holer and active magnetic bearing system. Magnetic actuators are designed for satisfying static load condition. The Performances of manufactured spindle system was examined for its static and dynamic stiffness, load capacity, and rotational accuracy. This spindle was run up to 70,000 rpm stably, which is 3.5 million DmN.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.586-589
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• 2005

Recently, the applications of unmanned system are steadily increasing. Unmanned automatic system is suitable for routine mission such as reconnaissance, environment monitoring, resource conservation and investigation. Especially, for the ocean environmental probe mission, many ocean engineers had scoped with the routine and even risky works. The unmanned surface vessel designed for sea probes can replace the periodic and routine missions such as water sampling, temperature and salinity measuring, etc. In this paper, an unmanned surface vessel was designed for ocean environmental probe missions. A classical and an adaptive fuzzy control system were designed and tested for the unmanned surface vessel. The design methodologies and performance of the surface vessel and fuzzy control algorithm were illustrated and verified with this unmanned vessel system designed for sea probes.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.132.4-132
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• 2001

Field robot represented by excavator can be applied for various kinds of working in manufacturing, construction, agriculture etc. because of the flexibility of its multi-joint mechanism and the high power of hydraulic actuators. In general, the dynamics of field robot have strong coupling, various kinds of non-linearity, and time varying parameters according to working conditions. Therefore, it is very difficult to describe the system well, and design controller systematically based on its model. This paper established the mathematical model of field robot driven by electro-hydraulic servomechanism and constructed the adaptive control system robust to external load variations. The proposed control system for the field robot was evaluated by the computer simulation, and the performance results of trajectory tracking were compared with that of PID control system.

• Proceedings of the KIEE Conference
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• 2002.04a
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• pp.179-182
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• 2002

The position information of the rotor are required while the SRG(Switched Reluctance Generator) is drived. The position information is generally provided by shaft encoder or resolver. But it is weak in the dusty, high temperator and EMI environment. Therefore, the sensor is able to required to eliminated from the SRG. In this paper, a estimation algorithm for the rotor position of the SRG is introducted and a constant DC-link voltage is controled by PID controller. The estimation algorithm is implemened by the adaptive sliding observer and that it is able to estimate the rotor position well is proved by the simulation.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.6
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• pp.633-641
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• 2015

Several complex processes that are employed in industries, such as shipping, power plants, and the petrochemical industry, involve time-varying behavior as well as strong nonlinear behavior during operation. The fixed-parameter proportional-integral-derivative (PID) controllers have difficulty in dealing with control problems that occur in such processes. In this paper, we propose a method of designing a nonlinear PID controller for industrial processes that exhibit a large number of nonlinearities and time-varying behavior. The gains of the nonlinear PID controller are characterized by a simple nonlinear function of the error and/or error rate depending on the process set-point and output. We tune the user-defined parameters using a genetic algorithm by minimizing the integral of time absolute error (ITAE) index. We verify the effectiveness of the proposed method by performing a comparison of the proposed method and two other nonlinear and adaptive methods that are employed for reference tracking, disturbance-rejection performances, and robustness to parameter changes on a continuously stirred tank reactor.

• Journal of IKEEE
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• v.3 no.2 s.5
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• pp.250-258
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• 1999

This paper presents a decentralized adaptive controller design for a Magnetically Levitated Fine Manipulator to follow the given trajectory as close as possible in spite of coupling effects between motion axes(degree of freedoms or subsystems). The present controller consists of two parts: the model reference controls based on known subsystems and the local adaptive controls. The former stabilizes the motion of the manipulator so as to follow that of the reference model. The latter reduces tracking errors due to coupling disturbances by adjusting the local gains to such levels that override interactions and assure the stability of the overall system. Through several experimental results, it has been shown that the decentralized adaptive control scheme has better tracking performances comparing to the PID controller case as well as good disturbance(coupling) rejection property.