• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.907-913
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• 2009

Pipeline construction is a highly repetitive and resource-intensive process that is exposed to various constraints and uncertainties in the working environment. Effective look-ahead scheduling based on the most recent project performance data can greatly improve project execution and control. This study enhances the traditional linear scheduling method with stochastic simulation to incorporate activity performance uncertainty in look-ahead scheduling. To facilitate the use of this stochastic method, a computer program, Stochastic Linear Scheduling Method (SLSM), was designed and implemented. Accurate look-ahead scheduling can help schedulers to better anticipate problem areas and formulate new plans to improve overall project performance.

• Journal of applied mathematics & informatics
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• 제42권2호
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• pp.223-235
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• 2024

In this paper, our primary focus revolves around the examination of a set of fractional stochastic models. Through our investigation, we can establish the presence of a solution and its distinctiveness. Additionally, we employ a moment-based algorithm to estimate the coefficients within these models and provide evidence that these estimations maintain their asymptotic characteristics. To support this claim, we conduct experimental studies using simulations and numerical examples.

• International Journal of Control, Automation, and Systems
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• 제1권1호
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• pp.1-10
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• 2003

This paper presents a high-precision magnetically levitated (maglev) stage to meet demanding motion specifications in the next-generation precision manufacturing and nanotechnology. Characterization of dynamic behaviors of such a motion stage is a crucial task. In this paper, we address the issues related to the stochastic modeling of the stage including transfer function identification, and noise/disturbance analysis and prediction. Provided are test results on precision dynamics, such as fine settling, effect of optical table oscillation, and position ripple. To deal with the dynamic coupling in the platen, we designed and implemented a multivariable linear quadratic regulator, and performed time-optimal control. We demonstrated how the performance of the current maglev stage can be improved with these analyses and experimental results. The maglev stage operates with positioning noise of 5 nm rms in $\chi$ and y, acceleration capabilities in excess of 2g(20 $m/s^2$), and closed-loop crossover frequency of 100 Hz.

• 자원ㆍ환경경제연구
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• 제20권2호
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• pp.357-379
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• 2011

경제환경의 글로벌화로 인해 외래종의 유입에 대한 관심이 증가하고 있다. 외래종은 동식물 개체 내지 미생물 수준에서 토착환경에 유입되어 침입종으로서의 유해한 영향을 미칠 수 있다. 본 논문은 확률적 확산과정을 이용하여 외래질병의 팬데믹 확률을 최소화하기 위한 최적제어 모형을 제시하며, 사회적 비용최소화 모형과 비교하였다. 실험적인 수치해석의 사례로 최근의 H1N1을 데이터를 이용하여 최적수준에 대한 비교정태 분석결과를 소개한다. 외래질병의 증가율이 높은 초기 시점부터 완전제어노력을 기울이는 것이 바람직하며, 사회적 비용을 최소화하는 접근방식보다는 보다 적극적인 초동대응 노력이 필요한 것으로 나타났다.

• 한국콘텐츠학회논문지
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• 제3권4호
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• pp.55-62
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• 2003

본 논문에서는 무선망에서 핸드오프 호의 분실확률을 줄일 수 있는 호 제어 기법을 제안한다. 제안한 기법은 진행 중인 시스템 용량인 유효로드와 임계치를 이용하여 호의 수락 여부를 결정하며 측정된 유효로드가 미리 정해진 임계치보다 크면 신규 호는 차단시키고, 핸드오프 호는 큐잉을 허용한다. 호 수락 제어 기법의 성능분석을 위하여 추계적 페트리 네트의 확장인 SRN 모델이 개발된다. SRN 모델링 기법은 성능분석을 위하여 필요한 마르코프 체인의 복잡한 해석적 분석대신 보상 개념에 의한 손쉬운 성능분석 수행방법을 보여준다.

• 한국지능시스템학회논문지
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• 제14권3호
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• pp.298-303
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• 2004

본 논문은 임의의 입력지연을 갖는 Takagi-Sugeno (T-S) 퍼지 시스템의 관측기 기반 출력궤환 제어 시스템을 논의한다. 설계된 연속시간 T-S 퍼지 관측기 시스템을 영차의 샘플/홀드 함수를 이용하여 이산시간 관측기를 설계한다. 이때 플랜트와 관측기의 출력에러가 제어기를 통하여 궤환되기 때문에 이산화 과정에서 발생한 에러를 보정할 수 있다. 여기에서 시스템의 제어 입력은 임의로 변화하는 유한개의 상태를 갖는 마코프 확률과정으로 표현한다. 생성된 시스템의 확률적 안정 가능성 조건은 선형 행렬 부등식의 형태로 표현한다. 이러한 결과를 2자유도 헬리콥터의 모델에 대한 모의실험을 통하여 효용성을 확인한다.

• 전자공학회논문지C
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• 제35C권3호
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• pp.79-89
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• 1998

The Error Back-Propagation(EBP) algorithm is widely applied to train a multi-layer perceptron, which is a neural network model frequently used to solve complex problems such as pattern recognition, adaptive control, and global optimization. However, the EBP is basically a gradient descent method, which may get stuck in a local minimum, leading to failure in finding the globally optimal solution. Moreover, a multi-layer perceptron suffers from locking a systematic determination of the network structure appropriate for a given problem. It is usually the case to determine the number of hidden nodes by trial and error. In this paper, we propose a new algorithm to efficiently train a multi-layer perceptron. OUr algorithm uses stochastic perturbation in the weight space to effectively escape from local minima in multi-layer perceptron learning. Stochastic perturbation probabilistically re-initializes weights associated with hidden nodes to escape a local minimum if the probabilistically re-initializes weights associated with hidden nodes to escape a local minimum if the EGP learning gets stuck to it. Addition of new hidden nodes also can be viewed asa special case of stochastic perturbation. Using stochastic perturbation we can solve the local minima problem and the network structure design in a unified way. The results of our experiments with several benchmark test problems including theparity problem, the two-spirals problem, andthe credit-screening data show that our algorithm is very efficient.

• 제어로봇시스템학회논문지
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• 제13권7호
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• pp.637-648
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• 2007

This paper presents a sensor fusion method based on indirect Kalman filter(IKF) for error compensation of low-cost inertial sensors and its application to the determination of attitude and position of small flying robots. First, the analysis of the measurement error characteristics to zero input is performed, focusing on the bias due to the temperature variation, to derive a simple nonlinear bias model of low-cost inertial sensors. Moreover, from the experimental results that the coefficients of this bias model possess non-deterministic (stochastic) uncertainties, the bias of low-cost inertial sensors is characterized as consisting of both deterministic and stochastic bias terms. Then, IKF is derived to improve long term stability dominated by the stochastic bias error, fusing low-cost inertial sensor measurements compensated by the deterministic bias model with non-inertial sensor measurement. In addition, in case of using intermittent non-inertial sensor measurements due to the unreliable data link, the upper and lower bounds of the state estimation error covariance matrix of discrete-time IKF are analyzed by solving stochastic algebraic Riccati equation and it is shown that they are dependant on the throughput of the data link and sampling period. To evaluate the performance of proposed method, experimental results of IKF for the attitude determination of a small flying robot are presented in comparison with that of extended Kaman filter which compensates only deterministic bias error model.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.107-110
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• 1996

Continuing advances in the formulation and solution of risk-sensitive control problems have reached a point at which this topic is becoming one of the more intriguing modern paradigms of feedback thought. Despite a prevailing atmosphere of close scrutiny of theoretical studies, the risk-sensitive body of knowledge is growing. Moreover, from the point of view of applications, the detailed properties of risk-sensitive design are only now beginning to be worked out. Accordingly, the time seems to be right for a survey of the historical underpinnings of the subject. This paper addresses the beginnings and the evolution, over the first quarter-century or so, and points out the close relationship of the topic with the notion of optimal cost cumulates, in particular the cost variance. It is to be expected that, in due course, some duality will appear between these notions and those in estimation and filtering. The purpose of this document is to help to lay a framework for that eventuality.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(II)
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• pp.1225-1228
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• 1987

It is shown that the singularly perturbed continuous-time system is led to two different discrete versions according to slow or fast sampling rates. The design of stabilizing feedback control of singularly perturbed discrete-time stochastic system is decomposed into the design of slow and fast controllers, which is combined to form the composite control. Composite control law is derived for the case of both single rate measurement and multirate measurement.