• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.2
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• pp.102-111
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• 2000

Methodology of volumetric error identification and compensation is presented to improve the accuracy of NC machine tools by using a reference artifact and a touch trigger probe. Homogeneous transformation matrix and kinematic chain are used for modeling the geo-metric and thermal errors of a three-axis vertical machining center. The reference artifact is designed and fabricated to identify the model parameters by machine tool metrology. Parameters in the error model are able to be identified and updated by direct measurement of the reference artifact on the machine tool under the actual conditions which include the thermal interactions of error sources. A volumetric error compensation system based on IBM/PC is linked with a FANUC CNC controller to compensate for the identified volumetric error in machining workspace.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.325-326
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• 2006

Recently, it is concentrated on productivity improvement in high speed operation by converting industries. Register error is becoming the one of the most issued problem. Moreover register control is the key to product flexible displays through roll-to-roll systems. This paper presents a derivation of register error modeling. And the dynamics of register error is simulated under various conditions. Register error is affected by both roll velocity and tension between the front and back span. And dynamics of register error is to be an interaction in succeeding spans.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.699-703
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• 1993

When the error path can be modeled as a pure delay, an adaptive algorithm for slowly time varying system is proposed to minimize the sound pressure level. This algorithm makes it possible to use the fittered-x LMS algorithm with on-line delay modeling of the error path. Another simple adaptive algorithm for pure tone noise is proposed which eliminates the cross term in the multiple error filtered-x LMS algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.943-946
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• 2000

Selective laser sintering(SLS) is a solid freeform fabrication process whereby a part is built layerwise by scanning a powder bed. The properties of metal powder are dependent on the heat, it is not easy to do the exact error compensation with analysis and estimation by modeling. This paper suggests that the error is compensated by experimental method and then the accuracy of shape is enhanced by revising of STL file. Also bonding force is measured by an experiment with change of process path.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.161.4-161
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• 2001

This paper presents adaptive control of robot manipulator using neuro-fuzzy controller Fuzzy logic is control incorrect system without correct mathematical modeling. And, neural network has learning ability, error interpolation ability of information distributed data processing, robustness for distortion and adaptive ability. To reduce the number of fuzzy rules of the FLS(fuzzy logic system), we consider the properties of robot dynamic. In fuzzy logic, speciality and optimization of rule-base creation using learning ability of neural network. This paper presents control of robot manipulator using neuro-fuzzy controller. In proposed controller, fuzzy input is trajectory following error and trajectory following error differential ...

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.797-800
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• 1992

Much experience and knowledge is needed in welding because there are many working parameters and quantitative description is difficult. Therefore, introduction of expert system based on such data base has been required. In this study, welding heat and shape of bead was controlled by fuzzy inference with the welding condition, position error and voltage and current error of robot. For this, torch trajectory of robot was generated by modeling the working data with CAD and then welding was carried out through down loading to robot. And working error was controlled by on-line communication.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.481-487
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• 2013

This paper presents an FIR (Finite Impulse Response) fixed-interval smoothing filter for fast and exact estimating state variables of a discrete nonlinear system with modeling uncertainty. Conventional IIR (Infinite Impulse Response) filter and smoothing filter can estimate state variables of a system with an exact model when the system is observable. When there is an uncertainty in the system model, however, conventional IIR filter and smoothing filter may cause large errors because the filters cannot estimate the state variables corresponding to the uncertain model exactly. To solve this problem, FIR filters that have fast estimation properties and have robustness to the modeling uncertainty have been developed. However, there is time-delay estimation phenomenon in the FIR filter. The FIR smoothing filter proposed in this paper makes up for the drawbacks of the IIR filter, IIR smoothing filter, and FIR filter. Therefore, the FIR smoothing filter has good estimation performance irrespective of modeling uncertainty. The proposed FIR smoothing filter is applied to the integrated navigation system composed of a magnetic compass based DR (Dead Reckoning) and a GPS (Global Positioning System) receiver. Even when the magnetic compass error that changes largely as the surrounding magnetic field is modeled as a random constant, it is shown that the FIR smoothing filter can estimate the varying magnetic compass error fast and exactly with simulation results.

• Journal of Advanced Navigation Technology
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• v.16 no.4
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• pp.602-610
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• 2012

Ionospheric delay error, one of main error sources in GPS signal, varies with signal frequency. Dual-frequency user uses L1, L2 frequency pseudorange to estimate the ionospheric delay, and there are errors caused by pseudorange measurement noise. So, filter is usually used to smooth the measurement. Weighted hatch filter can estimate optimal smoothed pseudorange measurement. But measurement noise model is needed to use this filter. In this paper, measurement noise modeling is conducted for NDGPS reference station. Using noise modeling result, weighted hatch filter estimate smoothed pseudorange measurement and ionospheric delay. Standard deviation of ionospheric dealy error drops to one-twenty fifth of non-filtered result.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.4
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• pp.112-123
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• 2017

Research for the inverse estimation of RF threats and the efficient electronic attack based on the parameters of the electronic information has been active in the electronic warfare (EW) situations. In this paper, an EW transmission simulator is constructed from the modeling of radar threats, EW receivers, and propagation environments with the collected electronic information in order to verify the performance of the inverse estimation algorithm in various and practical EW situations. In simulation results, we show that the range tracking error and angle tracking error are produced within ten meters and one degree, respectively. And also, we show that the changing relations between the angle tracking error and the parameters of the monopulse angle tracking radar such as the beamwidth and squint angle in simulation results correspond with those in the theoretical modeling. Accordingly, the constructed EW simulator can be used to observe the modifying characteristics of the electronic information in transmission environments, and then, to evaluate the performance of the inverse estimation system in various EW situations.

• The Journal of the Acoustical Society of Korea
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• v.33 no.2
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• pp.146-151
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• 2014

This paper analyzes the previous Anjok model of the Gayageum and describes a method to improve the frequency modeling based on previous model. In the previous work, relation between the fundamental frequency and Anjok's location on the body is assumed as an exponential function and these frequencies are integrated by a first-order leaky integrator. Finally, a parameter of the formula to calculate the fundamental frequency is obtained by applying integrated frequencies to the linear regression. This model shows 2.5 Hz absolute deviation on average and has maximum error 7.75 Hz for the low fundamental frequencies. In order to overcome this problem, this paper proposes that the Anjok's locations are grouped according to the rate of error increase and linear regression is applied to each group. To find the optimal parameter, the RMSE(Root Mean Square Error) between measured and calculated fundamental frequencies is used. The proposed model shows substantial reduction in errors, especially maximum three times.