• Journal of Positioning, Navigation, and Timing
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• v.6 no.2
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• pp.43-51
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• 2017

In this study, the effect of the steering vector model mismatch due to array uncertainties on the performance of array processing was analyzed through simulation, along with the alleviation of the model mismatch effect depending on array calibration. To increase the reliability of the simulation results, the actual steering vector of the array antenna obtained by electromagnetic simulation was used along with the Jahn's channel model, which is an experimental channel model. Based on the analysis of the power spectrum for each direction, beam pattern, and the signal-to-interference-plus-noise ratio of the beamformer output, the performance deterioration of array processing due to array uncertainties was examined, and the performance improvement of array processing through array calibration was also examined.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.5
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• pp.438-444
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• 2013

This paper presents the replication of a desired vibration response by iterative learning control (ILC) system for a vibration motion replication actuator. The vibration motion replication actuator has parameter uncertainties including system nonlinearity and joint nonlinearity. Vehicle manufacturers worldwide are increasingly relying on road simulation facilities that put simulated loads and stresses on vehicles and subassemblies in order to reduce development time. Road simulation algorithm is the key point of developing road simulation system. With the rapid progress of digital signal processing technology, more complex control algorithms including iterative learning control can be utilized. In this paper, ILC algorithm was utilized to produce simultaneously the six channels of desired responses using the Stewart platform composed of six linear electro-magnetic actuators with Halbach magnet array. The convergence rate and accuracy showed reasonable results to meet the requirement. It shows that the algorithm is acceptable to replicate multi-channel vibration responses.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1418-1425
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• 2014

In ultrasonic medical imaging, spatial compounding of images is a technique where ultrasonic beam is steered to examine patient tissues in multiple angles. In the conventional ultrasonic diagnostic imaging, the steering of the ultrasonic beam is achieved electronically using the phased array transducer elements. In this paper, a spatial compounding approach is presented where the ultrasonic probe element is rotated mechanically and the beam steering is achieved mechanically. In the spatial compounding, target position is computed using the value of the rotation axis and the transducer array angular position. However, in the process of the rotation mechanism construction and the control system there arises the inevitable uncertainties in these values. These geometric parameter errors result in the target position error, and the consequence is a blurry compounded image. In order to reduce these target position errors, we present a spatial compounding scheme where error correcting transformation matrices are computed and applied to the raw images before spatial compounding to reduce the blurriness in the compounded image. The proposed scheme is illustrated using phantom and live scan images of human knee, and it is shown that the blurriness is effectively reduced.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2003.05a
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• pp.87-91
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• 2003

It has well known that MUSIC and ESPRIT algorithms estimate angle of arrival(AOA) with high resolution by eigenvalue decomposition of the covariance matrix which were obtained from the array antennas. However, the disadvantage of MUSIC and ESPRIT is that they are computationally ineffective, and then they are difficult to implement in real time. The other problem of MUSIC and ESRPIT is to require calibrated antennas with uniform features, and are sensitive to the manufacturing facult and other physical uncertainties. To overcome these disadvantages, several method using neural model have been study. For multiple signals, those require huge training data prior to AOA estimation. This paper proposes the algorithm for AOA estimation by interconnected hopfield neural model. Computer simulations show the validity of the proposed algorithm. The proposed method does not require huge training procedure and only assigns interconnected coefficients to the neural network prior to AOA estimation.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.4
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• pp.411-419
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• 2005

In this paper, a sliding mode observer for solar array current estimation in the photovoltaic power generation system is presented. The solar array current estimation Information is obtained from the sliding mode observer and fed into the maximum power point tracker to update the reference voltage. The parameter values such as inverter dc link capacitances cm be changed up to 50$\%$ from their nominal values and the linear observer can't estimate the correct state values under the parameter variations and noisy environments. The configuration of sliding mode observer is simple, but it shows the robust tracking performance against parameter variations and modeling uncertainties. In this paper, the method for constructing the sliding mode observer using equivalent control input is presented and the convergence of the proposed observer is verified by the Lyapunov method. The mathematical modeling and the experimental results verify the validity of the proposed method.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.2
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• pp.131-138
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• 2004

In the proto design stage of a new car, the performances of an occupant protection system can be evaluated by CAE even though the real test should be carried out. The number of the real test is reduced by the exact predictions followed by the appropriate design recommendation. However, the existing researches using CAE in predicting the performances do not consider the uncertainties of parameters. That often leads to inconsistency between test and CAE. In this research, the robust design of a protection system such as airbag and load limiter is suggested considering the frontal crash. The parameter design scheme of the Taguchi method is introduced to obtain the robust design of arbitrary airbag and load limiter. It is performed based on the frontal crash test condition of US-NCAP with an arbitrary passenger car. The variances of the performances such as HIC, chest acceleration and probability of combined injury are calculated by the outer array and the Taylor series expansion. Through the analysis of the Taguchi method, the robust optimum is determined.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.350-353
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• 1994

This paper presents a method to calculate the characteristic root areas and loci band of control systems with uncertainties. First, equations of boundary curves of root areas in the case of additive and multiplicative perturbation are derived. Then, an algorithm for the calculation of the array of closed curves is presented. When the upper bound of the absolute values of frequency responses for the uncertain part, is also frequency-dependent, the frequency-dependent, terms are included in the characteristic equation of the nominal system. This lead to the boundary equations of the root, areas for control systems with frequency-dependent uncertainty. Numerical examples of the control systems with multiplicative perturbations including frequency-dependent terms are presented to verify this calculation method. Finally, its applications to the design of robust control systems, e.g., passive adaptive control systems are also discussed.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.649-655
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• 2007

In this paper, a time-delayed controller for position control of humanoid robot arms is designed and implemented on a field programmable gate array(FPGA) chip. The time-delayed control algorithm is simple to implement, and robust to reject disturbances. The time-delayed control method uses the one sample time-delayed previous information to cancel out uncertainties in the system. Since the sampling time is so fast with the current hardware technology, the time-delayed controller can be implemented. However, inertia values should be correctly estimated to have the better performance. The position tracking tasks of humanoid robot arms are tested to compare performances of several control algorithms including the time-delayed controller.

• Journal of The Korean Astronomical Society
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• v.27 no.2
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• pp.159-175
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• 1994

We have mapped the whole extent of a dark cloud Lynds 1251 in the emission of the J=1-0 transitions of $^{12}CO\;and\;^{13}CO$ using FCRAO's fifteen-beam array receiver in high angular resolution of 50'. We have derived physical parameters of L1251, discussed three different mass estimate techniques, and obtained a large range of mass, 600 to $6,000M_\bigodot$, depending on the techniques. The factor of 10 discrepancy between the virial and LTE masses is much larger than expected based on the uncertainties residing in two methods. The large virial mass may reflect the fact that L1251 is not gravitationally bound system as in the case of dark clouds in solar neighborhood. Two outflows are affecting the dynamics of cloud significantly but not enough to reshape the whole extent of the cloud. The small cloud, 'Stripe', which is apparently connected with main cloud, is not likely to be associated with L1251. The velocity gradient composed on this small cloud may be driven by other unknown sources. It is found that L1251 cloud itself is very quiescent except the two bipolar outflow regions.

• Journal of Navigation and Port Research
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• v.27 no.4
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• pp.465-469
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• 2003

It has well known that MUSIC and ESPRIT algorithms estimate angle of arrival(AOA) with high resolution by eigenvalue decomposition of the covariance matrix which were obtained from the array antennas, However, the disadvantage of MUSIC and ESPRIT is that they are computationally ineffective, and then they are difficult to implement in real time. the other problem of MUSIC and ESPRIT is to require calibrated antennas with uniform features, and are sensitive ti the manufacturing fault and other physical uncertainties. To overcome these disadvantages, several method using neural model have been study. For multiple signals, those methods require huge training data prior to AOA estimation. This paper proposes the algorithm for AOA estimation by interconnected Hopfield neural model. Computer simulations show the validity of the proposed algorithm. It follows that the proposed method yields better AOA estimates than MUSIC. Moreover, out method does not require huge training procedure and only assigns interconnected coefficients to the neural network prior to AOA estimation.