• International Journal of Precision Engineering and Manufacturing
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• v.3 no.3
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• pp.62-68
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• 2002

To satisfy the requirement of the one axis linear positioning system, which is following control of the desired trajectory without following error and is the high positioning accuracy, feed-forward loop having cogging force model is proposed. In the one axis linear positioning system with linear PM motor, cogging force acting as disturbance is modeled analytically. Analytic model of cogging force is verified by result measured from positioning system constructed with linear PM motor. Measured result is very similar with proposed analytic model. Cogging force model is used as feet forward loop in control scheme of linear positioning system. Cogging force feed-forward'loop is obtained from analytic model of cogging farce. Trajectory following error is reduced from 300nm to 100nm by applying the proposed cogging farce feed-forward loop. By using analytic model of cogging force, the control scheme is simplified. Also this analytic model is applicable to calculation of characteristic value of positioning system in design process.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.931-936
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• 1993

Optimal model following control scheme is to design the controller which makes the response of real system follow that of desirable model. This kind of design scheme is developed for first order system. We extends the scheme for second order system regarding the characteristics of mechanical second order system for vibration suppression of flexible structures. The model of mechanical second order system is obtained using suitable damping ratios and natural frequencies. Using this scheme, we can design the good controller which uses the characteristic of second order system. Numerical examples are presented which were used optimal model following control scheme.

• 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.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.359-363
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• 1994

In this paper the system called the inverse model compensation system is proposed as a system whose input-output transfer function can be regarded as that of a model with uncertainty in spite of including an unknown plant. And their to construct the robust model following system, which is of low sensitivity and robust stability, in order to control the inverse model compensation system is proposed. The simulation experiments show that the robust model following system including the inverse model compensation system is practical and useful as a system which controls unknown plants.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.2
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• pp.121-126
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• 2000

In the fast sampling limit the delta operator model tends to the analog system model. This fundamental property of the delta operator model unifies continuous and discrete time control system. In this paper we study robust linear optimal model following servo system in the presence of disturbances and parameter perturbations. A technique to directly design the generalized differential operator based unified control system that covers both differential operator based continuous time and delta operator based discrete time case is presented. The quadratic criterion function for a linear system is used to design the robust unified servo control system The characteristics of the proposed servo system are analysed and simulated to verify the robustness.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.123-128
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• 1998

This paper proposes design of LFT-based fuzzy controllers for model-following, which are better than the previous input-output linearization controllers, which are not able to follow the model system states and which do not guarantee the stability of all states. The method proposed in this paper provides a LFT-based Takagi-Sugeno(T-S) fuzzy controller with guaranteed stability and model-following via the following steps: First, using LFT(Linear Fractional Transformation) and T-S fuzzy model, controllers, are obtained. Next, error dynamics are obtained for model-following, and errors go to 0(zero). Finally, a T-s fuzzy controller that can stabilizxe the system with the requirement on the control input satisfied is obtained by solving the LMIs with the MATLAB LMI Control Toolbox and a model-following controller is obtained. Simulations are performed for the LFT-based T-S fuzzy controller designed by the proposed method, which show better performance than the results of input-out ut linearization controller.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.747-752
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• 1999

In the fast sampling limit, the delta operator model tends to the analog system model. This fundamental property of the delta operator model unifies continuous and discrete time control system. In this paper, we study robust linear optimal model following servo system in the presence of disturbances and parameter perturbations. A technique to directly design the generalized differential operator based unified control system that convers both differential operator based continuous time and delta operator based discrete time case is presented. The quadratic criterion function for a linear system is used to design the robust unified servo control. The characteristics of the proposed servo system are analysed and simulated to verify the robustness.

• 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.