• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.193-193
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• 2000

This paper proposes a dynamic observer that is applicable to linear time-invariant systems subject to unknown input, The proposed method utilities Che output feedback control structure to design unknown input observer. We name it as the dynamic unknown input observer(UIO). The dynamic UIO can be designed easily over the usual static UIO, and the system response could be improved.

• 소음진동
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• 제11권2호
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• pp.257-264
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• 2001

In this research, piezoelectric smart structures are applied for SEA(Statistical Energy Analysis), which is well known approach for high frequency analysis. A new input power measurement based on piezoelectric electrical power measurement is proposed and compared with the conventional method in SEA. As an example, a simple aluminum beam on which piezoelectric actuator is attached is considered. By measuring the electrical impedance and electrical current of the piezoelectric actuator, the electrical power given on the actuator is found and this is In turn converted into the mechanical energy. From the measured value of the stored energy of the beam, the Internal loss factor is calculated and this value shows a good agreement with that given by the conventional method as well as the theoretical value. To compare the coupling loss factor, L-shape beam system which consists of a aluminum beam subsystem and a steel beam subsystem coupled by three pin is taken as second example. The input power and stored energy of each subsystem are found by the proposed approach. The coupling loss factor found by the electrical input power obtained from the piezoelectric actuator exhibits similar trend to the value found by the conventional method as well as the theoretical value. In conclusion, the use of SEA for high frequency application of piezoelectric smart structures is Possible. Especially, the input power that is essential for SEA can be found accurately by measuring the electrical input power of the piezoelectric actuator.

• 전자공학회논문지SC
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• 제46권2호
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• pp.52-60
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• 2009

본 논문에서는 입력에 시간 지연이 존재하는 비선형 다중입출력(multi-input/multi-output (MIMO)) 시스템을 위한 디지털 제어기를 제안하였다. 다중 입력 시간 지연 비선형 시스템을 테일러의 추산 방법으로 이산화하고, 이 이산형 시스템을 일반적인 비선형 시스템으로 변환할 수 있다. 결과적으로, 일반 비선형 제어기를 이산형 시간 지연 시스템에 적용할 수 있다. 본 논문에서는 MAC 제어기를 설계하고 컴퓨터 시뮬레이션을 실시하여 제안된 방법의 성능을 검증하였다. 시뮬레이션의 결과 제안된 제어기는 비선형 다중입력 다중 시스템에 있어서 입력에 시간지연이 발생하더라도 시스템의 성능을 유지함을 확인할 수 있었다. 따라서 제안된 방법은 비선형 시간 지연 시스템의 제어에 유용함을 알 수 있다.

• 디지털산업정보학회논문지
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• 제19권1호
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• pp.109-118
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• 2023

Data-based analysis methods have become used more for estimating or predicting housing prices, and neural network models and decision trees in the field of big data are also widely used more and more. Neural network models are often evaluated to be superior to existing statistical models in terms of estimation or prediction accuracy. However, there is ambiguity in determining the input feature of the input layer of the neural network model, that is, the type and number of input features, and decision trees are sometimes used to overcome these disadvantages. In this paper, we evaluate the existing methods of using decision trees and propose the method of using decision trees to prioritize input feature selection in neural network models. This can be a complementary or combined analysis method of the neural network model and decision tree, and the validity was confirmed by applying the proposed method to house price estimation. Through several comparisons, it has been summarized that the selection of appropriate input characteristics according to priority can increase the estimation power of the model.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권7호
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• pp.378-388
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• 2000

In this paper, we propose Fuzzy Polynomial Neural Networks(FPNN) based on Polynomial Neural Networks(PNN) and Fuzzy Neural Networks(FNN) for model identification of complex and nonlinear systems. The proposed FPNN is generated from the mutually combined structure of both FNN and PNN. The one and the other are considered as the premise part and consequence part of FPNN structure respectively. As the consequence part of FPNN, PNN is based on Group Method of Data Handling(GMDH) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and self-organizing networks that can be generated. FPNN is available effectively for multi-input variables and high-order polynomial according to the combination of FNN with PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get better output performance with superb predictive ability. As the premise part of FPNN, FNN uses both the simplified fuzzy inference as fuzzy inference method and error back-propagation algorithm as learning rule. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using genetic algorithms. And we use two kinds of FNN structure according to the division method of fuzzy space of input variables. One is basic FNN structure and uses fuzzy input space divided by each separated input variable, the other is modified FNN structure and uses fuzzy input space divided by mutually combined input variables. In order to evaluate the performance of proposed models, we use the nonlinear function and traffic route choice process. The results show that the proposed FPNN can produce the model with higher accuracy and more robustness than any other method presented previously. And also performance index related to the approximation and prediction capabilities of model is evaluated and discussed.

• 전자공학회논문지
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• 제50권3호
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• pp.230-236
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• 2013

본 논문은 대표적인 손실 매질인 대지에 위치한 도체의 입력임피던스를 MATLAB을 이용한 자체 프로그램을 활용하여 계산하고, 그 결과를 나타내었다. 도체의 입력임피던스는 안테나 이론의 전자계 모델에서 유도된 포클링턴방정식에 모멘트법이 적용되어 계산되었다. 결과의 정확도를 높이기 위해서 기저함수와 가중함수가 삼각함수인 켈러킨법을 적용하였다. 대지에 위치한 도체의 영상분은 수정된 영상법을 적용하여 고려하였다. 도체의 전류분포에 대한 자체 제작한 프로그램 결과와 NEC 프로그램의 결과를 비교하여 프로그램의 신뢰성을 확인하였다. 대지에 위치한 도체의 길이가 1 m, 2 m인 경우에 도전율에 따른 임피던스를 주파수에 따라 시뮬레이션 하였다. 실제 대지에 설치된 도체의 입력임피던스와 위상을 측정하고 동일한 조건에서의 시뮬레이션 결과와 비교하였다.

• Journal of Mechanical Science and Technology
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• 제19권11호
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• pp.1975-1987
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• 2005

An input time delay always exists in practical systems. Analysis of the delay phenomenon in a continuous-time domain is sophisticated. It is appropriate to obtain its corresponding discrete-time model for implementation via digital computers. In this paper a new scheme for the discretization of nonlinear systems using Taylor series expansion and the zero-order hold assumption is proposed. The mathematical structure of the new discretization method is analyzed. On the basis of this structure the sampled-data representation of nonlinear systems with time-delayed multi-input is presented. The delayed multi-input general equation has been derived. In particular, the effect of the time-discretization method on key properties of nonlinear control systems, such as equilibrium properties and asymptotic stability, is examined. Additionally, hybrid discretization schemes that result from a combination of the scaling and squaring technique (SST) with the Taylor series expansion are also proposed, especially under conditions of very low sampling rates. Practical issues associated with the selection of the method's parameters to meet CPU time and accuracy requirements, are examined as well. A performance of the proposed method is evaluated using a nonlinear system with time delay maneuvering an automobile.

• 한국소음진동공학회논문집
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• 제15권9호
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• pp.1070-1076
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• 2005

Vibration test using the MAST(multi axial simulation table) provide a more reliable testing environment than any conventional one. The multi axial simulation could be possible with a advanced control algorithm and hardware supports so that most of the operation is automatically conducted by MAST system itself except the input information that is synthesized by the measured response signals. That means the reliability of the vibration test is highly depended on the quality of the input profile. In this paper, the optimal algorithm based on the energy method is introduced to construct a best combination of candidated input PSD data could be constructed. Since the optimal algorithm renders time information, the nitration fatigue test is completely possible for any measured signals one wants. The proposed method is explained with representing acquired road signals from the candidate input PSD obtained from a proving ground.

• 한국군사과학기술학회지
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• 제10권2호
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• pp.21-30
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• 2007

A practical method to design the input shaping which generates control command is proposed in this paper, We suggest an experimental technique considering human operator's target tracking error to improve aiming accuracy which significantly affects hit probability. It is known that stabilization performance is one of the most important factors for ground combat vehicle system. In particular, stabilization error of the manual target tracking system mounted on moving vehicle directly affects hit probability. To reduce this error, we applied input command shaping method using preprocessing filtering and functional curve fitting. First of all, we construct the human operator model to consider effects of human operator on our system. Input shaping curve is divided into several regions to get rid of the above problems and to improve the system performance. At example design part, we chose three steps of functional command curve and determine the parameters of the function by the proposed design method. In order to verify the proposed design method, we carried out the experiments with real plant of a fighting vehicle.

• 대한산업공학회지
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• 제36권3호
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• pp.154-163
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• 2010

Process monitoring of output variables affecting final performance have been mainly executed in semiconductor manufacturing process. However, even earlier detection of causes of output variation cannot completely prevent yield loss because a number of wafers after detecting them must be re-processed or cast away. Semiconductor manufacturers have put more attention toward monitoring process inputs to prevent yield loss by early detecting change-point of the process. In the paper, we propose the method to efficiently monitor functional input variables in multi-phase semiconductor manufacturing process. Measured input variables in the multi-phase process tend to be of functional structured form. After data pre-processing for these functional input data, change-point analysis is practiced to the pre-processed data set. If process variation occurs, key variables affecting process variation are selected using contribution plot for monitoring efficiency. To evaluate the propriety of proposed monitoring method, we used real data set in semiconductor manufacturing process. The experiment shows that the proposed method has better performance than previous output monitoring method in terms of fault detection and process monitoring.