• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1994.10a
• /
• pp.266-272
• /
• 1994

An essential ingredient in precision machining is a positioning system that responds quickly and precisely to very small input signal. In this paper, two different positioning systems were presented fot the precision positioning control. The one is a friction drive system, the other is a ballscrew system. The friction drive system was composed of an air sliding guide and a friction drive. The ballscrew system was made of a ballscrew and a linear guide. Nonlinear behaviors of the given systems tend to make the system inaccurate. The paper looked at the phenomena that has caused the positioning error. These apparently nonlinear phenomena can be attributed mainly to the presence of the nonlinear friction and slip effect plus the dynamic change from the microdynamic to the macrodynamic and form the macrodynamic to the microdynamic. For the control of the positioning system, the control algorithm based on a neural network is suggested. The FEL(Feedback Error Learning) controller can learn the inverse dynamics of a nonlinear system by using the neural network controller, and stabilize the system by a linear controller. In the experiment, PTP control is implemented withen the maximum error of 0.05 .mu.m ~0.1 .mu. m when i .mu.m step reference input is applied and that of maximum 1 .mu. m when 100 .mu.m step reference input is given. Sinusoidal inputs with the amplitude of 1 .mu.m and 100 .mu. m are used for the tracking control of the positioning system. Experimental results of the proposed algorithm are shown to be superior to those of conventional PD controls.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2562-2567
• /
• 2005

This paper suggests a new method discretization of nonlinear system using Taylor series expansion and zero-order hold assumption. This method is applied into the sampled-data representation of a nonlinear system with input time delay. Additionally, the delayed input is time varying and its amplitude is bounded. The maximum time-delayed input is assumed to be two sampling periods. Them mathematical expressions of the discretization method are presented and the ability of the algorithm is tested for some of the examples. And 'hybrid' discretization scheme that result from a combination of the ‘scaling and squaring' technique with the Taylor method are also proposed, especially under condition of very low sampling rates. The computer simulation proves the proposed algorithm discretized the nonlinear system with the variable time-delayed input accurately.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.5
• /
• pp.1240-1255
• /
• 1996

This paper suggests power optimization technique in multi-level SCPC system as a method for efficient utilization of limited satellite power. The power optimization is realized by optimal assignment of satellite input carrier powers considering interference and noise generated in up-link and down-link. The Fletcher-Powell algorithm searching minimum(or maximum) point using gradient information is used to detemine the optimal input carrier powers. To apply Flectcher-Powell algorithm mathematical descriptions and their partial derivatives to interference and nose are presented. Because a target, which should be optimized, is satellite input carrier power, amplitude of each carrier group will be assumed to be an independent variable. The performance criterion for optimal power assignmentis classified into 4 categories with respect to CNR of destination receiver earth station to meet the requirement for various satellite link environment. Simulation results for two-level, four-level and six-level SCPC system are presented.

• Journal of Mechanical Science and Technology
• /
• v.20 no.6
• /
• pp.759-769
• /
• 2006

This paper proposes a new method of discretization for nonlinear systems using a Taylor series expansion and the zero-order hold assumption. The method is applied to sampled-data representations of nonlinear systems with input time delays. The delayed input varies in time and its amplitude is bounded. The maximum time-delayed input is assumed to be two sampling periods. The mathematical expressions of the discretization method are presented and the ability of the algorithm is tested using several examples. A computer simulation is used to demonstrate that the proposed algorithm accurately discretizes nonlinear systems with variable time-delayed inputs.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.13 no.4
• /
• pp.67-73
• /
• 2013

This paper relates with the performance of VSCA adaptive equalization algorithm that is used for the minimization of the intersymbol interference due to the distortion which occurs in the time dispersive channel for the transmission of 16-QAM signal. In the conventional SCA, it is possible to compensates the amplitude and phase in the received signal that are mixed with the intersymbol interference by the constellatin dependent constant by using the 2nd order statistics of the transmitted signal. But in the VSCA, it is possible to the increase the equalization performance by adding the concept of distance adjusted approach for constellation matching. We compare the performance of VSCA and SCA algorithm by computer simulation. For this, the equalizer output signal constellation, residual isi, maximum distortion and MSE were used for perfomance comparison. It was confirmed that, the VSCA algorithm has better than the SCA in every performance index by computer simulation.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2001.06a
• /
• pp.89-92
• /
• 2001

In this paper, as a study of programmable software radio digital communication, we implemented ASK(Amplitude Shift Keying), FSK(Frequency Shift Keying), and PSK(Phase Shift Keying) modulation using programmable software(algorithm) of DSP(Digital Signal Processor). Moreover, it is possible to select one of those three modulation methods by realizing on single DSP. We adopted Motorola DSP56002 and Crystal CS4215(A/D and D/A converter) for our purpose. The DSP56002 is 24-bit and operates 20 MIPS at 40 MHz, and the CS4215 is 16-bit and supports the maximum 50 kHz sampling frequency.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2002.05a
• /
• pp.227-230
• /
• 2002

The Loose Part Monitoring System(LPMS) has been designed to detect, locate and evaluate detached or loosened parts and foreign objects in the reactor coolant system. In this paper, at first, we presents an application of the back propagation neural network. At the preprocessing step, the moving window average filter is adopted to reject the low frequency background noise components. And then, extracting the acoustic signature such as Starting point of impact signal, Rising time, Half period, and Global time, they are used as the inputs to neural network. Secondly, we applied the neural network algorithm to LPMS in order to estimate the mass of loose parts. We trained the impact test data of YGN3 using the backpropagation method. The input parameter for training is Rising Time, Half Period, Maximum amplitude. The result showed that the neural network would be applied to LPMS. Also, applying the neural network to the Practical false alarm data during startup and impact test signal at nuclear power Plant, the false alarms are reduced effectively. 1.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2006.05a
• /
• pp.219-222
• /
• 2006

본 논문에서는 ANFIS를 이용한 전자혈압계 측정알고리즘을 제안한다. 이를 위해 본 연구에서는 우선, 기존의 팔뚝형 커프와 수동 공기주입기 방식의 전자혈압 측정시스템을 구축하여 혈압 신호를 실시간으로 취득하였다. 다음단계로 취득된 실시간 혈압신호를 이용하여 최고혈압과 최저 혈압을 측정하기 위해 MAA(Maximum Amplitude Algorithm) 기법을 이용한다. 그러나, MAA기법은 개인의 특성을 고려하지 않고 일정한 비율을 고정시키므로 정확한 혈압을 측정하는데 한계가 있다. 따라서, 본 논문에서는 MAA에 의해 측정된 최고혈압과 최저혈압을 ANFIS를 이용하여 학습시키므로서 이러한 문제점을 해결하고자 한다. 제안된 알고리즘의 효율성을 보이기 위해 다양한 혈압신호에 대해 실험한 결과 기존의 MAA에 의한 방법보다 향상된 결과를 나타냈다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2011.05a
• /
• pp.559-562
• /
• 2011

In this research, We derived Recursive Least Squares(RLS) algorithm with adaptive maximum-likelihood channel estimate for digital pulse amplitude modulated sequence in the presence of intersymbol interference and additive white Gaussian noise. RLS algorithms have better convergence characteristics than conventional algorithms, LMS (Least Mean Squares) algorithms.

• Wind and Structures
• /
• v.18 no.3
• /
• pp.253-265
• /
• 2014

The platform and floating structure of spar type offshore wind turbine systems should be designed in order for the 6-DOF motions to be minimized, considering diverse loading environments such as the ocean wave, wind, and current conditions. The objective of this study is to optimally design the platform and substructure of a 3MW spar type wind turbine system with the maximum postural stability in 6-DOF motions as well as the minimum material cost. Therefore, design variables of the platform and substructure were first determined and then optimized by a hydrodynamic analysis. For the hydrodynamic analysis, the body weight of the system was considered, and the ocean wave conditions were quantified to the wave forces using the Morison's equation. Moreover, the minimal number of computation analysis models was generated by the Design of Experiments (DOE), and the design variables of the platform and substructure were finally optimized by using a genetic algorithm with a neural network approximation.