• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.234-234
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• 1999

The aim of this paper is to suggest a design method of the optimal model following control system using genetic algorithm (GA). This control system is designed by applying GA with reference model to the optimal determination of weighting matrices Q, R that are given by LQ regulator problem. The method to do this is that all the diagonal elements of weighting matrices are optimized simultaneously by GA, in the search domain selected adequately. And we design the model following control system to boi1er-turbine equipment by the proposed method. The model following control system designed by this method has the better command tracking performance than that of the control system designed by the trial-and-error method. The effectiveness of this control system is verified by computer simulation.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.338-340
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• 1993

In this paper, the method for designing a robust linear multivariable model following servo system is proposed. This model following servo system for the (n)th order reference input and the (n)th order disturbance is treated, and is designed so that the (n)th order response of the plant should be kept close to the (n)th order response of the given model by LQ(Linear Quadratic) optimal regulator approach. It is proved that the characteristics of the model following servo system is robust in the presence of the disturbances and the parameter perturbations of the plant dynamics.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1069-1072
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• 1996

In modern control engineering, the model following system is a typical method. The model following system's performance is due to algorithm of control law, accuracy of modeling to the plant, and dynamics of the reference model. But the determination of the reference model depends on knowledge of an expert. Using an expert system, the determination method of the reference model was proposed in this paper. So, the reference model can be selected by user who has no Knowledge of dynamics and parameters.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.57-62
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• 2004

This paper deals with a waypoint trajectory following problem for the tilt-rotor UAV under development in Korea (TR-KUAV). In this problem, dynamic model inversion based on the linearized model and Sigma-Phi neural network with adaptive weight update are involved to realize the waypoint following algorithm for the vehicle in the helicopter flight mode (nacelle angle=0 deg). This algorithms consists of two main parts: outer-loop system as a command generator and inner-loop system as stabilizing controller. In this waypoint following problem, the position information in the inertial axis is given to the outer-loop system. From this information, Attitude Command/Attitude Hold logic in the longitudinal channel and Rate Command/Attitude Hold logic in the lateral channel are realized in the inner-loop part of the overall structure of the waypoint following algorithm. The nonlinear simulation based on the TR-KUAV is carried out to evaluate the stability and performance of the algorithm. From the numerical simulation results, the algorithm shows very good tracking performance of passing the waypoints given. Especially, it is observed that ACAH/RCAH logic in the inner-loop has the satisfactory performance due to adaptive neural network in spite of the model error coming from the linear model based inversion.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.138-142
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• 2004

This paper proposes the design of the model following control system using the PID control structure. PID control system became model following control by inserting new pre-compensator in order to improve control performance in discrete-time region. Gain of the PID controller needs to be readjusted when response of system changes due to disturbance or load fluctuation. Performance of control system improves by joining neural network to PID control system because performance of control system depends largely on each PID gain in PID control system. And the games of the PID controller in the proposed control system are automatically adjusted by back-propagation algorithm of the neural network. Angular position of DC servo motor is selected as a plant in order to verify control performance in model following control. After it is applied to the position control system, it's performance is verified through computer experiment.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.372-375
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• 1996

In this paper, a designing method of model following control system for linear descriptor system with disturbances is proposed. The features of this method are:1) both the physical structure of the system and the physical system variables properties can be preserved because there is no necessary to make transformation of this system. 2) boundedness of internal states are proved by means of coprime factorization of descriptor system.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.876-881
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• 1987

This paper is concerned with a robust model following control scheme for manipulators which contains uncertain terms. Our method consists of nonlinear compensation and linear compensation. The former ensures the robustness of the plant, the later achieves both the desired model following response and the desired initial error convergence.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.373-376
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• 1986

This paper proposes a robust model following control system which realizes good properties such as asymptotic stability, disturbance rejection and model following with reduced sensitivity for plant parameter variation. This algorithm can be easily applied to the multivariable control systems and the control structure is simple. As an example the aircraft control system of a convair C-131B is designed and its characteristics are examined by simulation.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1165-1167
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• 1997

In this paper, the continuous sliding mode-model following(SM-MF) power system stabilizer(PSS) including closed-loop feedback(CLF) is extended to discrete-time sliding mode-model following(DSM-MF) PSS including CLF.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1171-1173
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• 1997

This paper presents the sliding mode observer-model following(SMO-MF) power system stabilizer(PSS) for unmeasurable plant state variables. This SMO-MF PSS can be obtained by combining the sliding mode-model following(SM-MF) including closed-loop feedback(CLF) with the linear foil-order observer(LFOO).