• Nonlinear Functional Analysis and Applications
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• 제27권4호
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• pp.813-837
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• 2022

In this paper we consider inverse problem for a general class of nonlinear stochastic differential equations on Hilbert spaces whose generating operators (drift, diffusion and jump kernels) are unknown. We introduce a class of function spaces and put a suitable topology on such spaces and prove existence of optimal generating operators from these spaces. We present also necessary conditions of optimality including an algorithm and its convergence whereby one can construct the optimal generators (drift, diffusion and jump kernel).

• Smart Structures and Systems
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• 제18권6호
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• pp.1251-1267
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• 2016

In this paper, Simple Adaptive Control (SAC) is used to enhance the seismic response of nonlinear tall buildings based on acceleration feedback. Semi-active MR dampers are employed as control actuator due to their reliability and well-known dynamic models. Acceleration feedback is used because of availability, cost-efficiency and reliable measurements of acceleration sensors. However, using acceleration feedback in the control loop causes the structure not to apparently meet some requirements of the SAC algorithm. In addition to defining an appropriate SAC reference model and using inherently stable MR dampers, a modification in the original structure of the SAC is proposed in order to improve its adaptability to the situation in which the plant does not satisfy the algorithm's stability requirements. To investigate the performance of the developed control system, a numerical study is conducted on the benchmark 20-story nonlinear building and the responses of the SAC-controlled structure are compared to an $H_2/LQG$ clipped-optimal controller under the effect of different seismic excitations. As indicated by the results, SAC controller effectively reduces the story drifts and hence the seismically-induced damage throughout the structural members despite its simplicity, independence of structural parameters and while using fewer number of dampers in contrast with the $H_2/LQG$ clipped-optimal controller.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2004년도 학술발표논문집
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• pp.67-72
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• 2004

Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate interval linear and nonlinear regression models combining the possibility and necessity estimation formulation with the principle of SVM. For data sets with crisp inputs and interval outputs, the possibility and necessity models have been recently utilized, which are based on quadratic programming approach giving more diverse spread coefficients than a linear programming one. SVM also uses quadratic programming approach whose another advantage in interval regression analysis is to be able to integrate both the property of central tendency in least squares and the possibilistic property In fuzzy regression. However this is not a computationally expensive way. SVM allows us to perform interval nonlinear regression analysis by constructing an interval linear regression function in a high dimensional feature space. In particular, SVM is a very attractive approach to model nonlinear interval data. The proposed algorithm here is model-free method in the sense that we do not have to assume the underlying model function for interval nonlinear regression model with crisp inputs and interval output. Experimental results are then presented which indicate the performance of this algorithm.

• 한국음향학회지
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• 제34권3호
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• pp.177-183
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• 2015

본 논문은 음성 통신 환경에서 스피커 모듈 비선형 특성 모델링과 긴 음향 반향 경로에서 효율적으로 동작하는 강인한 비선형 음향 반향 제거기를 제안한다. 제안하는 비선형 음향 반향 제거기는 sigmoid 전처리기를 사용하여 스피커 모듈의 비선형 특성을 모델링하며, 적은 시간 지연으로 긴 음향 반향 경로를 추정할 수 있도록 파티션 블록 주파수 영역 적응 필터를 사용한다. 실험을 통해 스피커 모듈의 비선형 특성이 발생하는 환경에서 제안 비선형 음향 반향 제거기는 기존 비선형 음향 반향 제거기에 비해 적은 연산량으로 우수한 성능을 보임을 확인하였다.

• 한국항해학회지
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• 제23권3호
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• pp.35-44
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• 1999

This research aims to seek active control of ball-beam position stability by resorting to neural networks whose layers are given bias weights. The controller consists of an LQR (linear quadratic regulator) controller and a neural networks controller in parallel. The latter is used to improve the responses of the established LQR control system, especially when controlling the system with nonlinear factors or modelling errors. For the learning of this control system, the feedback-error learning algorithm is utilized here. While the neural networks controller learns repetitive trajectories on line, feedback errors are back-propagated through neural networks. Convergence is made when the neural networks controller reversely learns and controls the plant. The goals of teaming are to expand the working range of the adaptive control system and to bridge errors owing to nonlinearity by adjusting parameters against the external disturbances and change of the nonlinear plant. The motion equation of the ball-beam system is derived from Newton's law. As the system is strongly nonlinear, lots of researchers have depended on classical systems to control it. Its applications of position control are seen in planes, ships, automobiles and so on. However, the research based on artificial control is quite recent. The current paper compares and analyzes simulation results by way of the LQR controller and the neural network controller in order to prove the efficiency of the neural networks control algorithm against any nonlinear system.

• Structural Engineering and Mechanics
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• 제34권6호
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• pp.685-702
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• 2010

In this paper, a nonlinear finite element procedure is presented for the dynamic analysis of reinforced concrete shell structures. A computer program, named RCAHEST (Reinforced Concrete Analysis in Higher Evaluation System Technology), was used. A 4-node flat shell element with drilling rotational stiffness was used for spatial discretization. The layered approach was used to discretize the behavior of concrete and reinforcement in the thickness direction. Material nonlinearity was taken into account by using tensile, compressive and shear models of cracked concrete and a model of reinforcing steel. The smeared crack approach was incorporated. The low-cycle fatigue of both concrete and reinforcing bars was also considered to predict a reliable dynamic behavior. The solution to the dynamic response of reinforced concrete shell structures was obtained by numerical integration of the nonlinear equations of motion using Hilber-Hughes-Taylor (HHT) algorithm. The proposed numerical method for the nonlinear dynamic analysis of reinforced concrete shell structures was verified by comparison of its results with reliable experimental and analytical results.

• 한국전산구조공학회논문집
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• 제20권2호
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• pp.147-155
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• 2007

본 논문에서는 수정 슬라이딩 모드제어기의 비선형 이력구조물의 지진응답 제어성능이 평가되었다. 수정 슬라이딩모드 제어는 제어력을 계산하기 위해 Lyapunov함수의 목표변화율을 이용하는 기법으로 기존 연구에서는 선형구조물에 대한 성능만이 조사되었다. 그러나 강진시 대부분의 구조물은 비선형 거동을 보인다는 점을 고려할 때 기존 연구의 결과는 실제 적용에 있어 제한점을 가지고 있다. Bouc-Wen 모델을 사용하여 구조물의 비선형 거동을 모델링 하였으며, 이력이선형 단자유도 구조물에 대한 통계해석과 비선형이력 면진구조물에 대한 해석결과는 제안된 수정 슬라이딩모드 제어알고리즘이 기존의 슬라이딩모드 제어기보다 우수한 성능을 가짐을 보여준다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.266-272
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• 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.

• 한국항공우주학회지
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• 제48권8호
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• pp.565-571
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• 2020

본 논문에서는 항공기 Wing-box 모델에 대한 비선형 구조해석의 계산을 정확하고 효율적으로 수행하기 위해 병렬계산 알고리즘을 개발하였다. 이를 위해 co-rotation 이론 기반 비선형 쉘 요소를 적용하였으며 요소기반 분할 병렬계산 알고리즘을 개발하였다. 기 개발 해석은 선행연구결과 및 기존 상용프로그램의 예측결과와 비교하여 정확성을 확인하였으며 병렬계산의 효율성을 분석하였다. 마지막으로 고세장비 날개 wing-box 구조에 적용하였으며 단방향 공력-구조 결합해석을 수행하였다.

• 항공우주시스템공학회지
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• 제9권4호
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• pp.23-30
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• 2015

The focal plane image stabilization for a camera is one of the most effective method that can increases the digital camera's image quality by compensating the vibration disturbance. The optical image stabilization can be implemented by making the focal plane to trace the path of incident light. To control the position of focal plane motion compensating stage precisely, a nonlinear control algorithm has been applied by considering coulomb friction which is nonlinear behavior of the compensator system. In our study, we have analyzed the hand shaking vibration using the gyro sensor, and made a mathematical model of compensating stage containing optical sensor and piezo-actuator. Then the nonlinear control algorithm has been designed and its performance has been verified by experiment. In this study, a friction driven peizo-electric actuator with $1{\mu}m$ resolution and 10mm/s speed has been used for stage movement.