• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.843-847
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• 1988

A new control method for position control of D.C. servo motor based on the variable structure control is presented. The desired trajectory satisfying the given performance requirement is used as the sliding curve. And the control input forcing the system to follow the desired model system is applied. As a result the method is robust to disturbance. The performance of the proposed controller is compared with that of the conventional state feedback controller through digital computer simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.10a
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• pp.192-197
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• 1992

The position error in multi-axis machine tools are due to many elements, such as the static friction, servo lag, a nonlinear disturbance, the gain mismatch between multi-axis controllers. In the work, modeling for the plant was carried out through the velocity response by the step input signal. Digital PI controllers, LQ optimal controllers and feedforward controllers are designed for a high tracking performance based on the model. The results of experimentation showed that the controllers worked properly.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.04a
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• pp.133-142
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• 1992

A kineamatic nonlinear multivariable laundher is modeled of which the azimoth and elevation axes are drived simultaneously and SISO and MIMO LQG/LTR controllers are designed and evaluated for this system. Also, the suitable command input function is suggested for the desired command following performance and the LQG/LTR control system with disturbances and load variation is evaluated for the entire operating range by computer simulation. It is found that the linear SISO LQG/LTR controller can be used for the kinematic nonlinear multivariable launder in the entire operating range and is effective for disturbance rejection and load variation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.72-72
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• 2000

This paper presents a methodology combining sliding mode control and fuzzy control to tune the boundary layer and input gain according to the system state. The equivalent control is designed such that the nominal system exhibits desirable dynamics, The robust control with fuzzy self-tuning is then developed to guarantee the reaching condition and reduce chattering phenomenon in the presence of parameter and disturbance uncertainties.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.6
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• pp.376-382
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• 1988

A small-signal low-frequency disturbance of the input line affects the regulated-output voltage of the series resonant converter. To mitigate the detrimental effect, the output feedback PI-controller is employed. Small-signal linear models are represented to characterize the closed loop series resonant converter system. Design equations for the PI-controller which satisfy stability and percent ripple conditions are derived from the closed-loop linear model. Experimental results are presented which show excellent correlation with theory.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.87.2-87
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• 2001

By the state transformation including independent outputs functions, a nonlinear process model can be decomposed into two subsystems; the one(design model) is described in output variables as new states and used for control system synthesis and the other(disturbance model) is described in the original unavailable states and its couplings with the design model are treated as uncertain time-varying parameters in the design model. Its existence with respect to the design model is ignored. So, the design model is an uncertain time-variant system. Control synthesis based on a reduced design model is a combined ...

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.33-38
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• 1996

In this paper, we present a robust H\ulcorner control design method for parameter uncertain systems that have delay in both state and control input. Through a certain algebraic Riccati inequality approach, a state feedback controller is obtained. The proposed state feedback controller stabilizes parameter uncertain delay systems and guarantees disturbance attenuation within a prescribed level. An illustrative example is given to demonstrate the results of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.3
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• pp.190-194
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• 2013

This paper presents experimental results of the attitude control for a two-rotor system with 3-DOF(degree-of-freedom). Two DC motors are equipped at the two ends of a rectangular beam to generate lift force and the relation between motor voltage and lift force is found experimentally. And inertial sensors are mounted at the center of the beam to measure the roll angle and a complementary filter is designed to get the angle during DC motors driving. A controller with nonlinear compensation, integrator and state feedback to achieve asymptotic tracking for a step input and reject input disturbance is designed and experimented.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.5
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• pp.837-844
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• 2013

This study performs erection of a pendulum hanging at a free end of an arm by rotating the arm to the upright position. A mathematical model of a rotary inverted pendulum system (RIPS) is derived. A brain emotional learning based intelligent controller (BELBIC) is designed and used as a controller for swinging up and balancing the pendulum of the RIPS. In simulations performed in the study, a pendulum is initially inclined at $45^{\circ}$ with respect to the upright position. A simulation is also performed for evaluating the adaptiveness of the designed BELBIC in the case of system variation. In addition, a simulation is performed for evaluating the robustness of the designed BELBIC against a disturbance in the control input.