• 한국전자통신학회논문지
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• 제18권5호
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• pp.935-944
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• 2023

본 연구에서는 신뢰성 연구에 적합하다고 알려진 Inverse-type(: Inverse-Exponential, Inverse-Rayleigh) 수명분포를 유한고장 NHPP(: Nonhomogeneous Poisson Process) 기반의 소프트웨어 개발비용 모형에 적용한 후, 성능을 결정하는 속성을 분석하였다. 또한, 모형의 효율성을 평가하기 위해 Goel-Okumoto 기본 모형과 함께 비교하였다. 고장 시간 데이터를 이용하여 모형의 성능을 분석하였고, 모수의 계산은 MLE(: Maximum Likelihood Estimation)를 적용하였다. 결론적으로, 첫째, 개발비용을 결정하는 m(t)를 분석한 결과, Inverse-Exponential 모형이 참값에 대한 오차가 적어 효율적이었다. 둘째, 개발비용과 함께 방출시간을 분석한 결과 Inverse-Rayleigh 모형이 가장 좋은 것으로 확인되었다. 셋째, 제안된 모형의 속성(m(t), 비용, 방출시간)을 종합적으로 평가한 결과, Inverse-Rayleigh 모형의 성능이 가장 우수하였다. 따라서 소프트웨어 개발자가 초기 프로세스에서 본 연구 데이터를 효율적으로 활용할 수 있다면, 비용에 영향을 미치는 속성들을 사전에 탐색하고 분석할 수 있을 것이다.

• 수산해양기술연구
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• 제29권4호
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• pp.279-285
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• 1993

Robot inverse kinematics solution is a complex nonlinear equation and very time-consuming task. This paper propose to use TSK fuzzy reasoning for solving robot inverse kinematics. A fuzzy model of inverse kinematics is identified by using input-output data and the model is used to solve the inverse kinematics. To show that, when used in robot inverse kinematics, fuzzy model is simple and generates a fairly accurate solution, a fuzzy model of inverse kinematics for PUMA robot is constructed.

• 설비공학논문집
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• 제20권3호
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• pp.205-212
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• 2008

This paper describes the application of an inverse building model to a calibrated forward building model using EnergyPlus program. Typically, inverse models are trained using measured data. However, in this study, an inverse building model was trained using data generated by an EnergyPlus model for an actual office building. The EnergyPlus model was calibrated using field data for the building. A training data set for a month of July was generated from the EnergyPlus model to train the inverse model. Cooling load prediction of the trained inverse model was tested using another data set from the EnergyPlus model for a month of August. Predicted cooling loads showed good agreement with cooling loads from the EnergyPlus model with root-mean square errors of 4.11%. In addition, different control strategies with dynamic cooling setpoint variation were simulated using the inverse model. Peak cooling loads and daily cooling loads were compared for the dynamic simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 A
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• pp.239-242
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• 2003

In this paper, we propose how to determine the optimal camera position using inverse kinematics of virtual link model and manipulability measure. We model the variable distance and viewing direction between a target object and a camera position as a virtual link. And, by using inverse kinematics of virtual link model, we find out regions that satisfy the direction and distance constraints for the observation of target object. The solution of inverse kinematics of virtual link model simultaneously satisfies camera accessibility as well as a direction and distance constraints. And we use a manipulability measure of active camera system in order to determine an optimal camera position among the multiple solutions of inverse kinematics. By using the inverse kinematics of virtual link model and manipulability measure, the optimal camera position in order to observe a target object can be determined easily and rapidly.

• 항공우주기술
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• 제13권2호
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• pp.99-107
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• 2014

다목적실용위성 2호/3호 위성자료를 이용하여 지상좌표를 결정하는 방법은 Physical Model과 RFM(Rational Function Model)의 두 가지 종류가 있다. 일반적으로 사용자에게 제공되는 모델은 RFM을 기반으로 한 RPCs(Rational Function Coefficients)이며, 이때 제공되는 RPCs는 지상좌표에서 영상좌표를 계산하는 계수이다. 사용자가 정사영상을 만들 경우에는 이 계수가 유용하나, 영상에서 임의의 영상기준점에 대응하는 지상좌표를 계산하거나, 위치정확도를 확인하기는 매우 어렵다. 본 논문은 다목적실용위성에서 제공되는 RPCs를 기반으로 Inverse RPCs를 해석하는 알고리즘과 해석된 Inverse RPCs를 기반으로 지상표고를 고려한 정밀 지상좌표 해석 알고리즘을 기술하고자 한다. 또한 Inverse RPCs의 해석된 정밀지상좌표 정확도와 Physical Model과의 차이를 계산하여 정확도를 평가하고자 한다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 추계학술대회논문집
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• pp.437-442
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• 2000

An alternative inverse feedback structure for adaptive active control of periodic noise is introduced for systems with nonminimum phase cancellation path. To obtain the inverse model of the nonminimum phase cancellation path, the cancellation path model can be factorized into a minimum phase term and a maximum phase term. The maximum phase term containing unstable zeros makes the inverse model unstable. To avoid the instability, we alter the inverse model of the maximum phase system into an anti-causal FIR one. An LMS predictor estimates the future samples of the noise, which are necessary for causality of both anti-causal FIR approximation for the stable inverse of the maximum phase system and time-delay existing in the cancellation path. The proposed method has a faster convergence behavior and a better transient response than the conventional FX-LMS algorithms with the same internal model control structure since a filtered reference signal is not required. We compare the proposed methods with the conventional methods through simulation studies.

• Structural Engineering and Mechanics
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• 제46권5호
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• pp.673-693
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• 2013

This paper presents a systematic design and training procedure for the feed-forward back-propagation neural network (NN) modeling of both forward and inverse behavior of a rotary magnetorheological (MR) damper based on experimental data. For the forward damper model, with damper force as output, an optimization procedure demonstrates accurate training of the NN architecture with only current and velocity as input states. For the inverse damper model, with current as output, the absolute value of velocity and force are used as input states to avoid negative current spikes when tracking a desired damper force. The forward and inverse damper models are trained and validated experimentally, combining a limited number of harmonic displacement records, and constant and half-sinusoidal current records. In general the validation shows accurate results for both forward and inverse damper models, where the observed modeling errors for the inverse model can be related to knocking effects in the measured force due to the bearing plays between hydraulic piston and MR damper rod. Finally, the validated models are used to emulate pure viscous damping. Comparison of numerical and experimental results demonstrates good agreement in the post-yield region of the MR damper, while the main error of the inverse NN occurs in the pre-yield region where the inverse NN overestimates the current to track the desired viscous force.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.443-446
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• 2003

Conventional disturbance rejection methods have to derive the inverse model of a system. However, the inverse model of n nonholonomic system is not unique, because an inverse it changes depending on initial conditions and desired values. A kind of internal model control (IMC) using feedback error learning is discussed for the motion control of nonholonomic mobile robots in this paper, The present method is different from a conventional IMC whose control system consists of an inverse model, a direct model and a filter. The present disturbance rejection method need not use a direct model, where the remaining two elements are composed of the same inverse model based on neural networks.

• 한국정보전자통신기술학회논문지
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• 제12권6호
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• pp.554-560
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• 2019

본 연구에서는 소프트웨어 신뢰성 분야에서 많이 사용하는 유한고장 NHPP Rayleigh 분포 모형과 NHPP Inverse Rayleigh 분포 모형을 소프트웨어 개발비용 모형에 적용한 후, 개발비용과 최적의 방출시간에 대한 속성을 비교, 분석하였다. 소프트웨어 개발비용의 속성을 분석하기 위하여 소프트웨어 고장시간 자료를 사용하였고, 모수추정은 최우추정법을 적용하였으며, 비선형 방정식은 이분법을 사용하여 계산하였다. 그 결과, Rayleigh 모형이 Inverse Rayleigh 모형보다 소프트웨어 개발비용이 비교적 적고, 소프트웨어 방출시점도 빨라서 상대적으로 우수한 모형임을 확인할 수 있었다. 본 연구를 통하여 기존 연구사례가 없는 Rayleigh 모형과 Inverse Rayleigh 모형의 개발비용 속성을 새롭게 분석하였으며, 더불어 소프트웨어 개발자들이 소프트웨어 신뢰도 향상 방법 및 개발비용의 속성을 탐색하는 데 필요한 기본지침으로 활용할 수 있을 것으로 기대한다.

• 제어로봇시스템학회논문지
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• 제7권11호
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• pp.891-895
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• 2001

An alternative inverse feedback structure for adaptive active control of periodic noise is introduced for systems with nonminimum phase cancellation path. To obtain the inverse model of the nonminimum phase cancellation path, the cancellation path model can be factorized into a minimum phase term and a maximum phase term. The maximum phase term containing unstable zeros makes the inverse model unstable. To avoid the instability, we alter the inverse model of the maximum phase system into an anti-causal FIR one. An LMS predictor estimates the future samples of the noise, which are necessary for causality of both anti-causal FIR approximation for the stable inverse of the maximum phase system and time-delay existing in the cancellation path. The proposed method has a faster convergence behavior and a better transient response than the conventional filtered-x LMS algorithms with the same internal model control structure since a filtered reference signal is not required. We compare the proposed methods with the conventional methods through simulation studies.