• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.685-686
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• 2008

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11a
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• pp.371-375
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• 2001

The concept of a new linear motor that uses piezo-stack actuator is demonstrated. The working principle is far different from the conventional inchworm motor. This motor is based on the self-moving cell concept. The linear motor has three cells and each cell is constructed with one piezo-stack actuator and a shell structure. A cell train is constructed by connecting these cells and the cell train is fitted into a guide way with a proper interference. The cell train moves along the guide way, by activating each cell in succession. The moving motion of the motor is tested. Since this linear motor uses piezo-stack actuator with unified clamping cell, it can produce fast speed, high resolution and large push force.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.649-654
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• 2003

This paper is focused on the research of the ultra precision linear motor by using piezo stack actuators. The development of linear motor which can be controlled nano or micro scale is necessary for the precision manufacturing. Self-moving-cell principle is used for the design of linear motor Self-moving-cell linear motor is consisted of three cell structures, and each cell has two shells and one piezo-stack actuator. Each cell can do clamping and moving by two shell structures. The shell structure deformation by piezo stack actuator can move the linear motor by losing the clamping between the shall and guideway. This paper presents the design, manufacturing and test of the motor.

• Journal of Sensor Science and Technology
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• v.28 no.2
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• pp.88-93
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• 2019

This paper is concerned with distributed fusion moving average prediction for continuous-time linear stochastic systems with multiple sensors. A distributed fusion with the weighted sum structure is applied to the optimal local moving average predictors. The distributed fusion prediction algorithm represents the optimal linear fusion by weighting matrices under the minimum mean square criterion. The derivation of equations for error cross-covariances between the local predictors is the key of this paper. Example demonstrates effectiveness of the distributed fusion moving average predictor.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.4
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• pp.7-13
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• 2010

Linear motors are efficient mechanism that offers high speed and positioning accuracy. By eliminating mechanical transmission mechanisms, much higher speeds and greater acceleration can be achieved without backlash or excessive friction. However, an important disadvantage of linear motor system is its high power loss and heating up of motor and neighboring machine components on operation. Therefore, it is necessary to design moving table with high stiffness, high efficiency and light weight construction. This paper presents the development of moving table using composite material. In order to develop light weight construction of moving table, finite element analysis is performed to find best moving table construction and composite stacking sequence. NASTRAN and MINITAB were used as the optimizer. A prototype for the moving table using composite material was created.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.10a
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• pp.408-413
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• 1997

The linear dynamic response of a simply supported uniform beam under a moving load of constant magnitude is investigated. When the ratio of the moving weight and the structure weight is small, moving object is considered as a concentrated or distributed moving force, that is large external loading can be considered as a concentrated or distributed moving masses. Result from the numerical solutions of the differential equations of motion are shown graphically. Moreover, when considering the maximum deflection for the mid-span of the hewn, the critical speeds of the moving load have been evaluated.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.211-217
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• 2011

This paper proposes a quasi-optimal linear DOA (Direction-of-Arrival) estimator which is necessary for the development of a real-time robot auditory system tracking moving acoustic source. It is well known that the use of conventional nonlinear filtering schemes may result in the severe performance degradation of DOA estimation and not be preferable for real-time implementation. These are mainly due to the inherent nonlinearity of the acoustic signal model used for DOA estimation. This motivates us to consider a new uncertain linear acoustic signal model based on the linear prediction relation of a noisy sinusoid. Using the suggested measurement model, it is shown that the resultant DOA estimation problem is cast into the NCRKF (Non-Conservative Robust Kalman Filtering) problem [12]. NCRKF-based DOA estimator provides reliable DOA estimates of a fast moving acoustic source in spite of using the noise-corrupted measurement matrix in the filter recursion and, as well, it is suitable for real-time implementation because of its linear recursive filter structure. The computational efficiency and DOA estimation performance of the proposed method are evaluated through the computer simulations.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.249-255
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• 2000

The design and test of an magnetostrictive linear motor(MLM) that operates based on self-moving cell concept is presented. The moving cell is composed of Terfenol-D linear actuator and a ring structure, and a cell train is constructed by connecting two cells in series. Since this motor uses the stroke of Terfenol-D actuators and friction force of the cells, it can essentially produce long stroke and large force. The overall performance of the MLM was measured in terms of speed and force. The pushing force is directly related with the friction force. This work is a proof-of-concept stage and investigation is necessary for realistic application.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.276-283
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• 2012

In this paper, a practical quasi-optimal DOA(direction of arrival) estimator is proposed in order to develop a one-axis gimbaled ultrasonic source tracker for mobile robot applications. With help of the gimbal structure, the ultrasonic moving source tracking problem can be simply reduced to the DOA estimation. The DOA estimation is known as one of the representative long-pending nonlinear filtering problems, but the conventional nonlinear filters might be restrictive in many actual situations because it cannot guarantee the reliable performance due to the use of nonlinear signal model. This motivates us to reformulate the DOA estimation problem in the linear robust state estimation setting. Based on the assumption that the received ultrasonic signals are noisy sinusoids satisfying linear prediction property, a linear uncertain measurement model is newly derived. To avoid the DOA estimation performance degradation caused by the stochastic parameter uncertainty contained in the linear measurement model, the recently developed NCRKF (non-conservative robust Kalman filter) scheme [1] is utilized. The proposed linear DOA estimator provides excellent DOA estimation performance and it is suitable for real-time implementation for its linear recursive filter structure. The effectiveness of the suggested DOA estimation scheme is demonstrated through simulations and experiments.

• Journal of Sensor Science and Technology
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• v.25 no.6
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• pp.418-422
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• 2016

A filtering algorithm based on the decentralized moving average Kalman filter with uncertainties is proposed in this paper. The proposed filtering algorithm presented combines the Kalman filter with the moving average strategy. A decentralized fusion algorithm with the weighted sum structure is applied to the local moving average Kalman filters (LMAKFs) of different window lengths. The proposed algorithm has a parallel structure and allows parallel processing of observations. Hence, it is more reliable than the centralized algorithm when some sensors become faulty. Moreover, the choice of the moving average strategy makes the proposed algorithm robust against linear discrete-time dynamic model uncertainties. The derivation of the error cross-covariances between the LMAKFs is the key idea of studied. The application of the proposed decentralized fusion filter to dynamic systems within a multisensor environment demonstrates its high accuracy and computational efficiency.