• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.693-696
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• 1999

This paper presents an analysis of the chaotic behavior in the discrete-time chaotic generator fabricated by CMOS technology. An approximated empirical equation is extracted from the measurement data of a nonlinear function block. Then the bifurcation diagram and Lyapunov exponent and time waveforms and frequency responses of the chaotic generator are calculated and simulated. And results of experiments in the chaotic circuit with the $\pm$2.5V power supply and clock rate of 10KHz are shown, and analysed.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.79-82
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• 2002

In this paper, we propose an adaptive repetitive control algorithm for the system the task of which is repetitive. The feedforward controller in the repetitive control system is modified by using the system parameter identifier in order to improve the convergence characteristics. The proposed algorithm is applied to the tracking control of a linear BLDC motor to which a periodic reference input is applied. It is illustrated by simulation results that the proposed adaptive repetitive control method yields better control performance than existing repetitive control even when modeling errors exist.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.1
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• pp.8-16
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• 1986

For digital process control, a low order discrete time modeling method is suggested and a direct digital control algorithm has been developed. The modeling method maintains process order of 3, while the sampling rate is doubled for fast response. With easy calculation it is possible to compute the model parameters and the controller gains. Controller tuning is possible on the spot. Simulation results show that this method has better performance than the deadbeat control agorithm.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.12
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• pp.1618-1624
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• 1988

In this paper, a robust discrete model reference adaptive controller is proposed using a generalized model reference adaptive algorithm for single-input single-output discrete systems. A signal dependent time-varying dead-zone is employed in a generalized adaptive control structure. This adaptive controller is shown to assure the boundedness of the signals of the system even in the presence of bounded external disturbance.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.12
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• pp.1610-1617
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• 1988

In this paper, a robust discrete-time adaptive control with compensation is proposed for single-input single-output discrete-time plants which have unmodeled dynamics. The stability of the overall system is studied using the conic sector stability theorems when a normalized constant gain parameter adaptation algorithm and a properly chosen compensation are used. An illustrative exmple shows that this compensation can also increase the parameter adaptation speed. And a method of compensation using the adaptive observation is also discussed.

• Proceedings of the Korean Society of Coastal and Ocean Engineers Conference
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• 1993.07a
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• pp.51-54
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• 1993

수조안 주 실험구간에서의 유황이 주로 파랑에 의해서 영향을 받는 경우에는 실험결과의 정확도는 바로 사용된 조파기의 성능에 의해서 좌우된다. 컴퓨터를 이용한 조파기 제어시스템을 구축하기 위해서는 특정 조파판 운동에 대한 조파판에서의 수면변화 양상을 정확히 예측할 필요가 있다. 본 연구에서는 복소수 해석을 통하여 조파판 전달함수를 재구성하였으며 시간영역에서 전달함수를 개별적으로 구현할 수 있는 수치 필터를 제시한다. (중략)

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.3
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• pp.619-625
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• 2000

A many control techniques have been proposed in order to improve the control performance of the discrete-time domain control system. In the position control system, the output of a controller is generally used as the input of a plant but the undesired noise is included in the output of a controller. Therefore there is a need to used a precompensator for rejecting the undesired noise. In this paper, The expanded I-PD control system with a precompensator is constructed. The precompensator and I-PD controller are designed by a neural network and these coefficients are changed automatically to be a desired response of system when the response characteristic of system is changed under a condition.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.511-518
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• 2021

In order to obtain a good tracking performance of the motor, it is necessary to design a controller that can respond to a disturbance by including a disturbance observer. The disturbance observer of the motor is designed to estimate the load torque and the back electromotive voltage based on the first-order low-pass filter. A PI controller and an IP controller were designed to compare the correlation between the disturbance observer and the controller and to obtain improved control performance. To check the performance of the designed observer and the controller, it was applied to a 120 [W] class BLDC motor. As a result, overshoot is reduced, and it can be seen that the steady-state error converges to zero.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.293-296
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• 1997

Robust stability conditions for discrete-time variable structure control is proposed. Conventionally the discrete-time variable structure control method with a variable structure uncertainty compensator approach requires a bounded changing rate of the uncertainties to ensure robust stability. However, when uncertainties vary as a function of state variables, which occur with parametric uncertainties, it is not reasonable to assume a bounded variation on the uncertainties. In this paper, uncertainties are assumed to consist of exogenous disturbances and parametric uncertainties. An uncertainty compensator is used to deal with the former, and a robust stability condition is derived using Small Gain Theorem for the latter.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.2
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• pp.67-72
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• 1996

This paper presents a parameter adaptive control law that stabilizes and asymptotically regulates any single-input, linear time-invariant, controllable and observable, discrete-time system when only the upper bounds on the order of the system is given. The algorithm presented in this paper comprises basically a nonlinear state feedback law which is represented by functions of the state vector in the controllable subspace of the model, an adaptive identifier of plant parameters which uses inputs and outputs of a certain length, and an adaptive law for feedback gain adjustment. A new psedu-inverse algorithm is used for the adaptive feedback gain adjustment rather than a least-square algorithm. The proposed feedback law results in not only uniform boundedness of the state vector to zero. The superiority of the proposed algorithm over other algorithms is shown through some examples.