• 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 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.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.4
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• pp.344-350
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• 1996

An adaptive predictive level control of waste heat steam boiler was studied by using mathematical models considering the inverse response. The simulation experiments of the model identification were performed by using linear and bilinear models. From the results of simulations it was found that the bilinear model represented the actual dynamic behavior of steam boiler very well. ARMA model was used in the model identification and the adaptive predictive controller. To verify the performance and effectiveness of the adaptive predictive controller used in this study the simulation results of the adaptive predictive level control for waste heat steam boiler based on bilinear model were compared to those of P, PI and PID controller. The results of simulations showed that the adaptive predictive controller provides the fast arrival to setpoint of liquid level.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.586-588
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• 2011

Adaptive feedforward control(AFC) is largely aimed for improving control performance of dynamic systems particularly involving periodic disturbance signals in engineering fields. This paper presents a novel hybrid AFC approach for specific systems with multiple disturbances in control input and state variables. The proposed AFC mechanism is hierarchically composed of the conventional AFC and a PID typed auxiliary control law in parallel. The former is generic to decrease periodic disturbance in control actuators and the latter is additionally constructed to overcome control deterioration due to time-varying uncertainty of given systems. We carry out numerical simulation to test reliability of the hybrid AFC system and compare its control performance with a well-known conventional AFC method in terms of time and frequency domains for proving of its superiority.

• Transactions of The Korea Fluid Power Systems Society
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• v.4 no.2
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• pp.1-6
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• 2007

During the last few decades, excavation automation has been investigated to protect the operator from the hazardous working environment and to relieve the cost of the skilled operator. Therefore, a number of modelling and controller design methods of the hydraulic excavator are proposed in many literatures to realize the excavation automation. In this article, a geometric approach far the multi-body system modeling is adopted to develop the excavator mechanism model that contains 4 kinematic loops and 12 links. Considering a simple soil mechanism model with a number of uncertain soil parameters, an adaptive trajectory tracking control strategy based on the developed excavator model is proposed. The improved performance of the designed controller over the simple PID controller is validated via the simulation study.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.10
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• pp.180-192
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• 1998

This paper introduces a new self-organizing fuzzy logic controller (SOFLC) for precision contour machining in the presence of large disturbances which adjusts both input and output membership functions simultaneously. The parameters of the proposed controller are self-tuned in real-time according to a continuous measurement of the performance of the controller itself and estimated disturbance values. The proposed controller as well as a conventional fuzzy logic controller and a PID controller were simulated and implemented on a 3-axis milling machine in contour milling. Both the simulations and experiments show that the self-organizing fuzzy logic controller has superior performance in terms of contour tracking accuracy compared with the other two controllers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.724-727
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• 2007

선박 운항 자동화 시스템은 선내 노동력 감소, 작업 환경 개선, 운항 안전성 확보 및 운항 능률의 향상을 목표로 하며, 궁극적으로는 운항 경제성확보를 위한 승선 인원의 최소화에 그 목적이 있다. 최근에는 적응 제어방법 등을 응용하여 선박의 비선형성을 보상하여 선박의 회두각 유지제어(Course Keeping Control), 항로 추적제어(Track Keeping Control), 롤-타각제어(Roll-Rudder Stabilization), 선박 위치제어(Dynamic Ship Positioning), 선박자동 접이안(Automatic Mooring Control) 등에 관한 연구를 수행하고 있으며 실제의 선박으로 대상으로 응용연구가 진행 중이다. 선박은 Steering Machine에 의해 조정되는 Rudder angle과 선박의 회두각의 관계는 비선형적이며, 선박의 Load Condition은 선박의 Parameter에 영향을 주는 비선형적인 요소로서 작용한다. 또한 외란요소인 파도의 유속(流速)과 방향, 풍속과 풍량 등이 비선형적인 형태로 작용하므로 선박의 운항을 힘들게 하는 요인이 된다. 따라서 선박의 운항시스템에는 비선형성을 극복할 수 있는 강인한 제어 알고리즘을 요구한다. 본 논문에서는 퍼지 알고리즘을 이용하여 선박의 비선형적인 요인 및 외란을 극복할 수 있는 선박의 자율운항 시스템을 설계하고 시뮬레이션을 통해 그 결과를 살펴보았다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.285-288
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• 2005

Neural networks are known as kinds of intelligent strategies since they have learning capability. There are various their applications from intelligent control fields; however, their applications have limits from the point that the stability of the intelligent control systems is not usually guaranteed. In this paper we propose a neuro-adaptive controller for robot manipulators using the radial basis function network(RBFN) that is a kind of a neural network. Adaptation laws for parameters of the RBFN are developed based on the Lyapunov stability theory to guarantee the stability of the overall control scheme. Filtered tracking errors between the actual outputs and desired outputs are discussed in the sense of the uniformly ultimately boundedness(UUB). Additionally, it is also shown that the parameters of the RBFN are bounded. Experimental results for a SCARA-type robot manipulator show that the proposed neuro-adaptive controller is adaptable to the environment changes and is more robust than the conventional PID controller and the neuro-controller based on the multilayer perceptron.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.3
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• pp.103-109
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• 2008

The work to raise the bridge plate by using two hydraulic cylinders is very dangerous when generating the unbalance state between cylinders. For solving this problem, one cylinder is forced to follow the trajectory of another cylinder instead of applying the same trajectory to two cylinders at once. In this paper, the control method for dynamic stable on lifting the bridge plate is proposed. The simulation model is derived by using commercial software, AMESim and MatLab/simulink. The PID controller is designed on one cylinder for following the reference trajectory and the adaptive controller is designed on another cylinder for tracking the displacement of one cylinder. The performance improvement is shown by comparing the simulation results through computer simulation.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.375-378
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• 1991

This paper presents a design method of synchronous generator excitation controller using self-tuning PID algorithm. Controller parameter is determined by using adaptive control theory in order to maintain optimal operation of generator under the various operating conditions. To determine the optimal parameter of controller. minimum variance algorithm using the recursive leastsquare(RLS) indentification method is adopted and the difference between the speed deviation with weighted factor and voltage deviation is used as the input signal of adaptive controller, which provides good damping and conversion characteristics. The results tested on a single machine infinite bus system verify that the proposed controller has better dynamic performances than conventional controller.