• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.76.3-76
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• 2001

In this paper, an adaptive disturbance compensation technique is used in a tracking problem, under which the tracking reference is unknown. Based on a simple disturbance observer that effectively estimates the low frequency components of disturbance, the feedforward compensation is applied in addition to the conventional feedback control. Under the proposed compensation method, sensitivity analysis is given to illustrate the effectiveness. Finally, the proposed method is applied to the tracking problem in an optical storage system.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.48.5-48
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• 2001

The resulting stabilizing controller in this paper consists of the disturbance estimator and the gain scheduled controller. The disturbance estimator tracks the unknown external disturbance and its derivative information in the closed-loop control system using fuzzy logic based adaptation law. Moreover, the gains of the stabilizing controller are appropriately scheduled according to the estimated values. Furthermore, since the estimation law is combined with the stabilizing controller in the closed control loop, it asymptotically minimizes the estimation error. In order to conrm the usefulness of the proposed control scheme, it is applied to the magnetic suspension systems.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.382-382
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• 2000

The external force disturbance is the one of the main causes that deteriorate the performance of the magnetic suspension. Thus, this paper develops a fuzzy estimator for gain scheduling control of magnetic suspension systems suffering from the unknown disturbance. The proposed fuzzy estimator computes the disturbance injected to the plant and the gain scheduled controller generates the corresponding stabilizing control input associated with the estimated disturbance. In the simulation results we confirm the novelty of the proposed control scheme comparing with the other method using a feedback linearization.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.156-160
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• 1993

This paper presents a controller design to coordinate a robot manipulator under unknown system parameters and bounded disturbance inputs. To control the motion of the manipulator, an inverse dynamics control scheme is applied. Since parameters of the robot manipulators such as mass and inertia are not perfectly known, the difference between the actual and estimated parameters works as a disturbance force. To identify the unknown parameters, an inproved adaptive control algorithm is directly derived from a chosen Lyapunov's function candidate based on the Lyapunov's Second Method. A robust control algorithm is devised to counteract the bounded disturbance inputs such as contact forces and disturbing force coming from the difference between th actual and the estimated system parameters. Numerical examples are shown using three degree-of-freedom planar arm.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.254-255
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• 2023

This paper discovers a robust managerial strategy for a stochastic inventory of perishable products, where the model experiences changing factors including inner parameters and an external disturbance with unknown form. An analytical solution for the optimization problem can be obtained by applying the Hamilton-Bellman-Jacobi equation, however the policy result cannot completely suppress the oscillation from the external disturbance. Therefore, an intelligent approach named Radial Basis Function Neural Networks is applied to estimate the unknown disturbance and provide a robust controller to manipulate the inventory level more effective. The final results show the outstanding performance of RBFNN controller, where both the estimation error and control error are guaranteed in the predefined limit.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.476-476
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• 2000

This paper deals with an estimation method far sideslip angle by using an unknown input observation technique in 4WS passenger car systems. Firstly, a 4WS vehicle model with 3DOP is derived under the constant velocity and same tyre's properties. The induced model is transformed into the linear state space model with considering the external disturbance. Secondly, an unknown input observer is introduced and its property which estimating the states of system without any disturbance information is shown. Lastly, the estimated sideslip angle of the 4WS system is verified through numerical simulation.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.1
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• pp.58-62
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• 1999

This paper shows that is possible to identify the system's input-output dynamics exactly in the presence of unknown periodic disturbances for the Active Engine Mount Control Application .The disturbance frequencies and waveforms can be completely unknown and arbitrary. Only measurements of a control excitation signal and the disturbance-contaminated response are used for identification. Examples are given to illustrate the method, including the identification and vibration control of active engine mount for automobile.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.228-232
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• 2004

This paper is to identify the position of random disturbance on flexible dynamic system, and the position of the piezo ceramic actuator 0 minimize tip response. Correlation of the output signals from each parts on flexible system is used to identify the position of random disturbance. Except the correlation with an output signal from the position of random disturbance, other correlations have time delay. This is a base idea to identify the position on this study.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.84-86
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• 2005

Adaptive tracking, disturbance rejection and power system stabilizer. First, this paper deals with power system stabilization problem using asymptotic tracking of arbitrary smooth bounded reference output signals, with simultaneous rejection of disturbances generated by an unknown linear exosystem. Second, this paper presents a power system stabilizer(PSS) using nonlinear adaptive observer backstepping controller.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.615-620
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• 2015

DOB (Disturbance Observer) is an useful control method for estimating the disturbance applied to dynamic systems. Disturbance observer can be used to implement a robust control system to generate a control input for rejecting the disturbance, and it can be also used to estimate the disturbance to obtain information. The system that uses disturbance estimation is investigated for high performance control such as automatic door systems, walking robot and electric power steering system in vehicles. In this paper, a novel disturbance observer which is called disturbance and current observer for estimating load torque in the motor system is proposed. The difference between the DOB for disturbance rejection and DCOB is mathematically verified. Current and angular velocity are required for estimating the load torque of the motor in DOB. However, the DCOB can estimate load torque and current without current sensor. DCOB is designed based on modeling of the motor system. Appropriate Q-filter is selected and the applicability of DCOB is verified by simulation. The estimated disturbance and current of the electric motor can be verified without current sensor, as experiments of the actual motor system.