• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.359-359
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• 2000

Generally, level control in the steam generator of a nuclear power plant is difficulty process control, because the low power operating can lead nonminimum phase characteristics(swell and shrink phenomenon) and flow measurement are unreliable and nonlinear characteristics. This paper presents a framework for solving this problem based on the constrained linear model predictive control and introduces the design of method for the level of the controller in the entire operating power of the steam generator, and compares with conventional PI controller.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.4
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• pp.220-225
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• 1988

A class of adaptive controllers with integral action is proposed, which may riject the offset due to any load disturbance on the plant. Effective integral action and robust identification against the offset can be achieved via the zero-gain predictor. The system is improved, in this paper, to be of more generalized structure, and the detuning control weight which can cope with nonminimum-phase systems is tuned on-line. Discrete-time versions of the improved system are developed, which may be more flexible for the choice of the design parameters. The resulting control systems may also be shown to be robust to the unmodelled dynamics.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.468-471
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• 1997

In this paper, we investigate the time-sampling effects on the digital implementation of singular perturbation based STT autopilot with excellent performance and propose a compensation method for the time-sampling effects. In digitization of analog STT autopilot, it is found that the stability margin of the fast dynamics is mostly affected to lead to rapid decrease. Under the this analysis, a composite digital controller with additional compensator for fast dynamics is proposed to improve the time-sampling effect and a simulation verifies the result.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.407-412
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• 1990

This note presents a novel algorithm for a continuous-time direct adaptive pole placement control for single-input single-out nonminimum phase systems. Although the resulting overall closed-loop system is locally stable, assumptions about parameter convergence or the nature of the external input are not considered.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.78-82
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• 1986

In the process control applications of self tuning control, a major concern of the control problem is to handle an offset caused by load disturbances and random steps occuring at random instance of time. Conventionally an integrator is incorperated in the forward path of the controller to eliminate such an offset. But this approach causes a difficulty if the adaptive part of the resultant controller is to be evaluated. In this paper a method of analyzing the adaptive system and improving the offset effect is suggested for a class of referance model method in the self tuning adaptive control system.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.9
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• pp.1046-1050
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• 1988

A direct adaptive control algorithm for discrete-time SISO systems with arbitrary zeros is presented in a general way by making use of reference model. A linear equation error model is formulated for estimating both the controller parameters and the auxiliary parameters. With this algorithm, asyptotic tracking within an arbitrarily small error can be achieved.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.4
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• pp.262-267
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• 2000

In this paper, the magnitude of undershoot and overshoot in a prototype second order system with one positive real zero is computed by the analytic methods. Also, it will be shown that the peak times of the undershoot and overshoot can be calculated using the impulse and step response of the second order system. Three different cases are investigated: underdamped(p<ζ<1), critically damped(ζ=1) and overdamped(ζ>1) cases. We deal with the undamped(ζ=0) case as a special case of the underdamped. And a compensation method is proposed to reduce undershoots of the nonmininmun phase system using feedforward compensator.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.418-421
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• 1997

A control synthesis scheme is presented for nonlinear single-input-single-output (SISO) systems with parametric uncertainty which have completely unstable zero dynamics. The approach involves the derivation of an input-output linearizing control law which achieves internal stability for a nonlinear minimum phase approximation to the original system using Fliess normal form. A vector of unknown constant parameters is also considered. A Lyapunov-based additional control law is shown to stabilize the full system.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.6
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• pp.89-96
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• 1985

A pole-placement control of discrete, deterministic, single-input single-output nonmini-mum phase systems is considered using a model reference type approach. The proposed pole-placement controller is designed in the parameter form to make the transfer function of the controller equal to that of the reference model with only single variable polynomial S(q-1). The proposed adaptive pole-placement controllr is designed with the true system para-meters by applying the adaptation method to the proposed pole-placement controller.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.6
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• pp.56-66
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• 1998

This paper investigates a neuro-controller combined in parallel with a conventional linear controller of PID type in order to control nonminimum phase systems more efficiently. The objective is to minimize overall position errors as well as to maintain small undershooting. A costfunction is proposed with two conflict objectives. The neuro-controller is trained off-line with evolutionary programming(EP) in such a way that it becomes optimal by minimizing the given cost function through global evaluation based on desired control performance during the whole training time interval. However, it is not easy to find an optimal solution which satisfies individual objective simultaneously. With the concept of Pareto optimality and EP, we train the proposed controller more effectively and obtain a valuable set of optimal solutions. Simulation results show the efficacy of the proposed controller in a viewpoint of improvement of performance of a step response like fast settling time and small undershoot or overshoot compared with that of a conventional linear controller.