• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.2 s.95
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• pp.169-175
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• 2005

In this paper, a novel vibration control scheme for a single-link flexible manipulator system without using a vibration feedback sensor is proposed. In order to achieve the vibration information of the flexible link, a reaction moment estimator based on the dynamic characteristics of the flexible manipulator is proposed. While the manipulator is maneuvering the reaction moment is reciprocally acting on the flexible link and the hub inertia due to the vibration of the link. A sliding mode controller based on the equivalent rigid body dynamics corresponding to the proposed flexible manipulator is then augmented with the reaction moment estimator to realize a decentralized control system. The reaction moment estimator is implemented via the first order low pass filter. The performance of the proposed control scheme is verified by computer simulation and experiment.

• Journal of the Korean Society for Precision Engineering
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• v.8 no.3
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• pp.64-72
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• 1991

This paper deals with the state estimator and controller. All state variables' feedback in the system were used to improve electro hydraulic servo sysem were used to improve electro hydraulic servo system's responese charact- eristics. Many gains of the state variables'and estimator's are produced by the algebraic Riccati equation, and every state variables'optimal gain and estimator gain is selected by trial and error method. For the designed estimator performance's examination, this paper simulate the time response for the step input, the reduced velocity output in subjected to load torque, and the time response for the step input in changing the inertiamoment.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.420-422
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• 1998

In this paper, we propose a position-speed control of servo system with a state estimator. And also we utilized two mass modelling in order to deals with real system accurately. The overall control system consists of two parts: the position-speed controller and state estimator. The Kalman filter applied as state - feedback controller is an optimal state estimator applied to a dynamic system that involves random perturbations and gives a linear,unbiased and minimun error variance recursive algorithm to estimate the unknown state optimally. Therefore we consider the error problem about the servo system modelling, the measurement noise at low-speed ranges a stochastic system, and implement a optimal state observer. Performance of the proposed state estimator are demonstrated by computer simulations.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.5
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• pp.259-267
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• 2019

This paper proposes a structure of a variable impedance control system based on sensor-less external force estimator of industrial manipulators for cyber physical production systems (CPPS). To implement CPPS, a feedback system is constructed by using the robot operating system (ROS) and an external force estimator which is designed to measure the external force applied to the manipulator without a force sensor. Based on the robot dynamics, the robot-human cooperating system for the cyber physics production system is implemented through a controller that changes the impedance characteristics of the manipulator according to the situation using the external force estimator. Simulation and experimental results verify the effectiveness of the proposed control system.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.106-110
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• 2001

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 system suffering from the unknown disturbance. The propose fuzzy estimator computes the disturbance injected to the plant the gain scheduled controller generates the corresponding stabilizing control input associated with 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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• 2005.06a
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• pp.275-280
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• 2005

The principal context of this research is the approach to an artificial neural network algorithm which solves multivariable nonlinear equation systems by estimating the state of line power flow. First a dynamical neural network with feedback is used to find the minimum value of the objective function at each iteration of the state estimator algorithm. In second step a two-layer neural network structures is derived to implement all of the different matrix-vector products that arise in neural network state estimator analysis. For hardware requirements, as they relate to the total number of internal connections, the architecture developed here preserves in its structure the pronounced sparsity of power networks for which state the estimator analysis is to be carried out. A principal feature of the architecture is that the computing time overheads in solution are independent of the dimensions or structure of the equation system. It is here where the ultrahigh-speed of massively parallel computing in neural networks can offer major practical benefit.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.92-94
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• 2004

In the previous work, we proposed a new stability criterion for the stability of switched linear systems. By the proposed criterion, we could simply check the stability of switched linear systems because the criterion is applicable to each individual subsystem without need to consider the overall system. Using this criterion, we provided the methods that design a state feedback control when full states are available. In this paper, we apply the same criterion to the case when full states are not available. Unlike existing method such as dwelling time analysis, the proposed method is suitable to a fast switching process because there is no need to consider dwelling time. And we can easily achieve designing multi-controller, multi-estimator, and the supervisor by means of the proposed method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.248-254
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• 1996

A disturbance rejection controller using eccentricity filtering and LQ control techniques is proposed to alleviate significantly the effect of roll eccentricity in multivariable cold-rolling processes. Fundamental problems such as process time delay inherent in exit thickness measurement and non-stationary characteristics of roll eccentricity signals can be overcome by the proposed control method. The filtered instantaneous estimate of roll eccentricity may be exploited to improve instantaneous estimate of the exit thickness variation based on roll force and roll gap mearsurements, and a feedforward compensator is augmented as a reference for a gaugemeter thickness estimator. And, LQ feedback controller is combined with eccentricity filter for the attenuation of the exit thickness variation due to the entry thickness variation. The simulation results show that eccentricity components have been significantly eliminated and simultaneously other distrubances also have been attenuated.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.87.1-87
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• 2001

For a plant subject to several kinds of disturbances in the plant input side, we consider a problem of designing a controller based on the disturbance cancellation. The conventional loop transfer recovery (LTR) technique can not be used since the extended system consisting of the plant and the disturbance model is not necessarily stabilizable. We propose a new LTR technique that can be applied for our problem. As a target of the LTR, we choose a state feedback controller using a disturbance estimator. We find an LTR procedure based on the Riccati equation formalism where the stochastic model contains the filter gain matrix of the disturbance estimator in the target. The procedure recovers the target feedback ...

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.231-234
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• 1996

This paper considers the output regulation problems on uncertain systems. Using NR-estimator(on-line), a family of equilibrium points for the uncertain system is computed. The state variables of the closed loop system track the average value of the obtained equilibrium manifold by dynamic state feedback control.