• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1981-1986
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• 2004

In this study, the basic motor control system had been investigated. The controller for this study consists of two main parts, a feedforward controller part and a feedback controller part. Each part will deals with different control problems. The feedback controller deals with robustness and stability, while the feedforward controller deals with response speed. The feedforward controller, used to solve the tracking control problem, is adaptable. To make such a tracking perfect, an adaptive law based on Feedback Error Learning (FEL) is designed so that the feedforward controller becomes an inverse system of the controlled plant. The novelty of FEL method lies in its use of feedback error as a teaching signal for learning the inverse model. The theory in $H^{\infty}$-Control is selected to be applied in the feedback part to guarantee the stability and solve the robust stabilization problems. The simulation of each individual part and the integrated one are taken to clarify the study.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1911-1916
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• 2005

In this study, the basic motor control system had been investigated. The Discrete-Time Feedback Error Learning (DTFEL) method is used to control this system. This method is anologous to the original continuous-time version Feedback Error Learning(FEL) control which is proposed as a control model of cerebellum in the field of computational neuroscience. The DTFEL controller consists of two main parts, a feedforward controller part and a feedback controller part. Each part will deals with different control problems. The feedback controller deals with robustness and stability, while the feedforward controller deals with response speed. The feedforward controller, used to solve the tracking control problem, is adaptable. To make such the tracking perfect, the adaptive law is designed so that the feedforward controller becomes an inverse system of the controlled plant. The novelty of FEL method lies in its use of feedback error as a teaching signal for learning the inverse model. The PD control theory is selected to be applied in the feedback part to guarantee the stability and solve the robust stabilization problems. The simulation of each individual part and the integrated one are taken to clarify the study.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.699-701
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• 2004

This paper proposes the algorithm of servo- writing based on feedback error learning neural networks. The controller consists of feedback controller using PID and feedforward controller using gaussian radial basis function network. Because the RBFNs are trained by on-line rule, the controller has adaptation capability. The performance of the proposed controller is compared to that of conventional PID controller. Proposed algorithm shows better performance than PID controller.

• Journal of IKEEE
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• v.11 no.4
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• pp.213-218
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• 2007

We consider a web transport system. The objective of this paper is to design the output feedback controller such that the controller can track a desired tension and processing speed on web transport system. We propose the new design method using observer and feedback linearization technique. The proposed method use a nonlinear feedback to transform to linear system and high gain observer to estimate the state value. We show that the proposed controller can achieve the control object using only output. We show a performance of controller via the simulation.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.8 s.101
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• pp.954-961
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• 2005

This paper is concerned with the implementation of auto-tuning positive position feedback controller using a digital signal processor and microcontroller. The main advantage of the positive position feedback controller is that it can control a natural mode of interest by tuning the filter frequency of the positive position feedback controller to the natural frequency of the target mode. However, the positive position feedback controller loses its advantage when mistuned. In this paper, the fast fourier transform algorithm is implemented on the microcontroller whereas the positive position feedback controller is implemented on the digital signal processor. After calculating the frequency which affects the vibrations of structure most, the result is transferred to the digital signal processor. The digital signal processor updates the information on the frequency to be controlled so that it can cope with both internal and external changes. The proposed scheme was installed and tested using a beam equipped with piezoceramic sensor and actuator. The experimental results show that the auto-tuning positive position feedback controller proposed in this paper can suppress vibrations even when the target structure undergoes structural change thus validating the approach.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.498-503
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• 2005

This paper is concerned with the implementation of adaptive positive position feedback controller using a digital signal processor and microcontroller The main advantage of the positive position feedback controller is that it can control a natural mode of interest by tuning the filter frequency of the positive position feedback controller to the natural frequency of the target mode. However, the positive position feedback controller loses its advantage when mistuned. In this paper, the fast fourier transform algorithm is implemented on the microcontroller whereas the positive position feedback controller is implemented on the digital signal processor. After calculating the frequency which affects the vibrations of structure most the result is transferred to the digital signal processor. The digital signal processor updates the information on the frequency to be controlled so that it can cope with both internal and external changes. The proposed scheme was installed and tested using a beam equipped with piezoceramic sensor and actuator. The experimental results show that the adaptive positive position feedback controller proposed in this paper can suppress vibrations even when the target structure undergoes structural change thus validating the approach.

• The Journal of Korea Robotics Society
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• v.6 no.4
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• pp.317-322
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• 2011

An augmented state feedback controller for a Wheeled Inverted Pendulum (WIP) is proposed in this research. The augmented state feedback controller is able to keep the WIP returning to the origin. Generally, the WIP has both stable and unstable equilibrium points. To keep the WIP over the unstable equilibrium point, the WIP consistently is being controlled. A simple state feedback controller is letting the WIP out of the origin when the center of gravity of the WIP locates out of the schematic center line. In some case of applications, it may not be desirable that the WIP is drifting out of the initial location. The proposed augmented state feedback controller is able to keep the WIP at the initial location whether its center of gravity lies out of the center line or not. Numerical simulations are carried out to show the validation of the augmented sated feedback controller.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.145-148
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• 1990

In this paper, the problem of designing a feedback controller for a robotic manipulator, which is activated by a D.C. motor through a gear train and a flexible shaft or chain, is considered. When the response of the closed loop control system is relatively slow, a satisfactory controller may be designed as a PID controller. As the speed of the control system increases, however, the spring effect of the linkage becomes profound, and as a result, the transient response exhibits a substantial oscillation. To eliminate this oscillation, it is necessary to design the controller based on at least a fourth order system model. This, in turn, requires the feedback of the entire state variables. In practice, however, only the position of the manipulator and the velocity of the motor are readily measurable. The state variable reconstruction method or a state observer cannot be used because of the system nonlinearities such as the Coulomb frictions. In this study, an alternative controller, which is based on delayed feedback of the output variable only, is proposed, and a successful delayed feedback controller is designed and implemented on an actual experimental manipulator.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.52 no.8
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• pp.363-367
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• 2003

Robust control for feedback control system is needed according to the highest precision of industrial automation. However, when a feedback control system has an effect of disturbance, it is very difficult to guarantee the robustness of control system. As a compensation method solving this problem, in this paper, Hybrid control method of feedback and Differential Supervisory controller is presented. A Feedback Controller is operated as a main controller, A Differential Supervisory Controller is a controller which operates only when some undesirable phenomena occur, e. g., when the error hits the boundary of constraint set. The robust control function of Differential Supervisory Controller, as a assistant controller is operated when state is unstable by disturbance. it demonstrated by speed control of motor.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.257-260
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• 1997

In this paper, the double inverted pendulum having a single actuator is built and the controller for the system is proposed. The lower link is hinged on the plate to free for rotation in the x-z plane. The upper link is connected to the lower link through a DC motor. The double inverted pendulum built can be kept upright posture by controlling the position of the upper link even though the proposed inverted pendulum has no actuator in lower hinge. The algorithm to control the inverted pendulum is consisted of a state feedback controller within a linearizable range and a fuzzy logic controller coupled with a feedback linearization control for the rest of the range. Concept of the virtual work is employed to drive the linearlized model for the state feedback controller. The feedback linearization controller drives a DC motor with the modified reference joint angle from the fuzzy controller which adjusts a upright posture of a proposed pendulum system. Finally, the experiments are conducted to show the validity of the proposed controller.