• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6B
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• pp.559-568
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• 2002

In this paper, we studied on combining the control of transmission fates and power for the real system where a finite set of transmission rates are used. In [1], the combined control of transmission rates and power was first researched, and suggested the Selective Power Control (SPC) algorithm. However, it can't guarantee the minimum rate to each user and results in frequent changes of rate due to oscillation of the SIR (Signal to Interference Ratio) values. As a main purpose of this paper, we derive a formulation model and propose a distributed iteration algorithm to solve these problems. To evaluate the performance of the proposed algorithm, we carried out numerical analysis and computational experiments. The results indicate that the proposed algorithm achieves better throughput than conventional one by keeping the low average transmission power.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.5 no.3
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• pp.1-12
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• 1985

The linear tracking theory has a great merit that its solution can be analytically obtained under the quadratic performance measure. However, this theory has not been applied to reservoir system operation yet, because the tracking assumes no boundness of the control and state vectors. This paper presents deriving the optimal control law and solving the Riccati equations for the discrete time horizon, and its application to the real system. And the additional necessary conditions for the saturated vectors of the control and/or state are also derived using the concept of the Pontryagin's minimum principle. The logic and its algorithm in this work are not so positive to give a general solution. In fact, it is a matter of modeling in terms of relative magnitude of disturbance and time-step size. However its application to the real environment of the Han river, which comprises six major reservoirs in series/parallel, demonstrated satisfactory results over 36 monthly stages.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.1
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• pp.117-120
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• 2008

This paper investigates the convergence condition of ADILC(iterative learning control with advanced output data) for nonminimum phase systems. ADILC has simple learning structure including both minimum phase and nonminimum phase systems. However, for nonminimum phase systems, the overall time horizon must be considered in input update law. This makes the dimension of convergence condition matrix large. In this paper, a new sufficient condition is proposed to satisfy the convergence condition. Also, it has been shown that this sufficient condition can be satisfied although it is not full impulse response.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.3
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• pp.76-85
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• 1998

In this paper, a fuzzy tuning method of a control gain in the discrete-time repetitive controller is proposed for precise tracking control of a system whose reference signal is repetitive. The control gain is modified by fuzzy rules which use the magnitude and the variation ofthe maximum output error in the previous repetitive period. The proposed method is applied to a direct drive 2-axis SCARA-type robot and, it is illustratedby computer simulations and real-time experimentation that better performance can be obtained that the fixed gain-based repetitive controller.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.225-227
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• 2006

This note investigates the convergence condition of ADILC (iterative learning control with advanced output data) for nonminimum phase systems. ADILC has simple learning structure including both minimum phase and nonminimum phase systems. However, for nonminimum phase systems, the overall time horizon must be considered in input update law. This makes the dimension of convergence condition matrix large. In this paper, a new sufficient condition is proposed to satisfy the convergence condition. Also, it has been shown that this sufficient condition can be satisfied although it is not full impulse response.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.133-135
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• 1997

In this paper, a fuzzy tuning discrete-time repetitive control is suggested for a robot manipulator. Real-time implementation of this type of repetitive controller is also performed for a 2 link direct drive robot by using a real-time control system which consists of a real-time OS(Spectra), a single board computer, a communication board and an analog input/output board. First, it is shown that the tracking error is effectively reduced by discrete-time repetitive control. Second, the convergence performance is shown to be much improved by the suggested controller using real-time experimentations.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.7
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• pp.56-65
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• 1997

In this paper, we propose a reference input odification-type iterative learning control law for a class of discrete-time nonlinear systems and prove the convergence of the output error. We can get the high-precision in case of the trajectroy control when the proposed control law is properly combined with a feedback controller, and we can easily implement the learning control law compared to the control input modification-type learning control law. To show the validity and the convergence perfodrmance of the proposed control law, we perform experimentations on the trajectroy control and rejection of periodic disturbance for a 2-axis SCARA-type direct drive robot.