• 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 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 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.

• Journal of Sensor Science and Technology
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• v.19 no.5
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• pp.375-384
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• 2010

In this paper, we proposed a new shaft distortion correction system having an adaptive PID controller using displacement sensors, which is adaptively reflecting variations of shaft strength owing to irregular heat treatment during an annealing process and sensitivity to the seasonal temperature changes. Generally, the shafts are annealed by heat treatment in order to enlarge the strength of the shaft, which causes an distortion of a shaft such as irregular bending of the shaft. In order to correct such a distortion of the shaft, a mechanical pressure is properly impacted to the distorted shaft. However, the strength of every shaft is different from each other owing to irregular annealing and seasonal temperature changes. Especially, the strength of a thin shaft such as a car transmission shaft is much more sensitive than that of a thick shaft. Therefore, it is very important for considering the strength of each shaft during correction of the car transmission shaft distortion in order to generate proper mechanical pressure. The conventional PID controller for the shaft distortion correction system does not consider each different strength of each shaft, which causes low productivity. Therefore, we proposed a new PID controller considering variations of shaft strength caused by seasonal temperature changes as well as irregular heat treatment and different cooling time. Three displacement sensors are used to measure a degree of distortion of the shaft at three different location. The proposed PID controller generates adaptively different coefficients according to different strength of each shaft using appropriately obtained pressure times from long-term experiments. Consequently, the proposed shaft distortion correction system increases the productivity about 30 % more than the conventional correction system in the real factory.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.3
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• pp.26-30
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• 2001

Controller refinement scheme to improve the performance of a conventional system automatically in frequency domain is proposed. The controller automatic tuning method features using experimental frequency responses of the conventional closed-loop system, the conventional controller, and the improved closed-loop system, instead of poorly modeled plant due to non-linearities and disturbances. The improved closed-loop system characteristics is automatically acquired by the con-ventional closed-loop system characteristics and the proposed performance index in system bandwidth. And the proper controller is realized by least squares approximation in frequency domain. To testify the usefulness of the approach, the path tracking control of robot arm is performed. Experimental results and analytic results are well-matched.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.136-139
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• 2000

Controller refinement scheme to improve the performance of a conventional system automatically in frequency domain is proposed. The controller automatic tuning method features using experimental frequency responses of the conventional closed-loop system, the conventional controller, and the improved closed-Imp system; instead of poorly modeled plant due to non-linearities and disturbances. The improved closed-loop system characteristics is automatically acquired by the conventional closed-loop system characteristics and the proposed performance index in system bandwidth. And the proper controller is realized by least squares approximation in frequency domain. To testify the usefulness of the approach, experimental results of robot path-tracking control applied with various controllers is used, and then is analyzed with respect to a equivalent proportional controller. Experimental results and analytic results are well-matched.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.99-104
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• 2001

Discrete-time controller design is proposed using feedback system identification in frequency domain. System Stability imposed by a new controller is checked in the function of a conventional closed-loop system, instead of a poorly modeled plant due to non-linearity and disturbance as well as unstable components, etc. The stability of the system is evaluated in view of Popov criterion. All the equations are formulated in the framework of the discrete-time system. Simulation results are shown on the plant with input saturation components, DC disturbance and a pure integration.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.664-669
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• 2001

Continuous-time controller design is proposed using feedback system identification in frequency domain. System stability imposed by a new controller is checked in the function of a conventional closed-loop system, instead of a poorly modeled plant due to non-linearity and disturbance as well as unstable components, etc. The stability of the system is evaluated in view of Nyquist stability. All the equations are formulated in the framework of the discrete-time system. Simulation results are shown on the plant with input saturation and DC disturbance.

• 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.

• 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.