• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.617-621
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• 2012

This paper studies asymptotic consensus problem for linear multi-agent systems. We propose a distributed state feedback control algorithm for solving the problem under fixed and undirected network communication. In contrast with the conventional algorithms that use global information (e.g., graph connectivity), the proposed algorithm only uses local information from neighbors. The principle for achieving asymptotic consensus is that, for each agent, a distributed update law gradually increases the coupling gain of LQR-type feedback and thus, the overall stability of the multi-agent system is recovered by the gain margin of LQR.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.06a
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• pp.49-50
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• 2006

The studies on Cu CMP have focused on material removal and its mechanisms. Although many studies have been conducted on the mechanism of Cu CMP, a study on uniformity in Cu CMP is still unknown. Since the aim of CMP is global and local planarization, the approach to uniformity in Cu CMP is essential to elucidate the Cu CMP mechanism as well. The main purpose of the experiment reported here was to investigate the roles of slurry components in the formation of the uniformity in Cu CMP. All the results of in this study showed that the uniformity in Cu CMP could be controlled by the contents of slurry components.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.620-626
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• 2004

For general nonlinear processes, it is difficult to control with a linear model-based control method and nonlinear controls are considered. Among the numerous approaches suggested, the most rigorous approach is to use dynamic optimization. Many general engineering problems like control, scheduling, planning etc. are expressed by functional optimization problem and most of them can be changed into dynamic programming (DP) problems. However the DP problems are used in just few cases because as the size of the problem grows, the dynamic programming approach is suffered from the burden of calculation which is called as 'curse of dimensionality'. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach is proposed by Bertsekas and Tsitsiklis (1996). To get the solution of seriously nonlinear process control, the interest in NDP approach is enlarged and NDP algorithm is applied to diverse areas such as retailing, finance, inventory management, communication networks, etc. and it has been extended to chemical engineering parts. In the NDP approach, we select the optimal control input policy to minimize the value of cost which is calculated by the sum of current stage cost and future stages cost starting from the next state. The cost value is related with a weight square sum of error and input movement. During the calculation of optimal input policy, if the approximate cost function by using simulation data is utilized with Bellman iteration, the burden of calculation can be relieved and the curse of dimensionality problem of DP can be overcome. It is very important issue how to construct the cost-to-go function which has a good approximate performance. The neural network is one of the eager learning methods and it works as a global approximator to cost-to-go function. In this algorithm, the training of neural network is important and difficult part, and it gives significant effect on the performance of control. To avoid the difficulty in neural network training, the lazy learning method like k-nearest neighbor method can be exploited. The training is unnecessary for this method but requires more computation time and greater data storage. The pH neutralization process has long been taken as a representative benchmark problem of nonlin ar chemical process control due to its nonlinearity and time-varying nature. In this study, the NDP algorithm was applied to pH neutralization process. At first, the pH neutralization process control to use NDP algorithm was performed through simulations with various approximators. The global and local approximators are used for NDP calculation. After that, the verification of NDP in real system was made by pH neutralization experiment. The control results by NDP algorithm was compared with those by the PI controller which is traditionally used, in both simulations and experiments. From the comparison of results, the control by NDP algorithm showed faster and better control performance than PI controller. In addition to that, the control by NDP algorithm showed the good results when it applied to the cases with disturbances and multiple set point changes.

• Journal of applied mathematics & informatics
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• v.5 no.2
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• pp.433-448
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• 1998

In this study we use inexact Newton-like methods to find solutions of nonlinear operator equations on Banach spaces with a convergence structure. Our technique involves the introduction of a generalized norm as an operator from a linear space into a par-tially ordered Banach space. In this way the metric properties of the examined problem can be analyzed more precisely. Moreover this approach allows us to derive from the same theorem on the one hand semi-local results of kantorovich-type and on the other hand 2global results based on monotonicity considerations. By imposing very general Lipschitz-like conditions on the operators involved on the other hand by choosing our operators appropriately we can find sharper error bounds on the distances involved than before. Furthermore we show that special cases of our results reduce to the corresponding ones already in the literature. Finally our results are used to solve integral equations that cannot be solved with existing methods.

• Proceedings of the KSPS conference
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• 1996.10a
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• pp.542-547
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• 1996

Prosodic characteristics of natural speech, especially intonation, in many cases represent specific feelings of the speaker at the time of the utterance, with relatively vast variations of speaking styles over the same text. We analyzed a collected speech corpus, recorded with ten Slovene speakers. Interpretation of observed intonation contours was done for the purpose of modelling the intonation contour in synthesis process. We devised a scheme for modeling the intonation contour for different types of intonation units based on the results of analyzing intonation contours. The intonation scheme uses a superpositional approach, which defines the intonation contour as the sum of global (intonation unit) and local (accented syllables or syntactic boundaries) components. Near-to-natural intonation contour was obtained by rules, using only the text of the utterance as input.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2989-2991
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• 2000

TS 퍼지 모델은, 복잡한 비선형 시스템을 효과적으로 표현할 수 있는 주요한 근사 모델 중 하나이다. TS 퍼지 모델링을 위한 기존의 학습 방법론들은 대부분 전역적 근사 오차를 최소화하는 것을 목적으로 하는데, 이러한 경우에는 결과로서 얻어지는 75 퍼지 모델의 국소모델들이 근사 대상 시스템의 국소적 특성을 제대로 표현 할 수 없는 상황이 발생할 수 있다. 따라서 본 논문에서는 이러한 특성을 고려하여 새로운 학습 알고리즘을 제시함으로써 전역 지역적 성능을 동시에 향상시킬 수 있는 TS 퍼지 모델을 구하고자 한다 모델을 구하는데 있어서는 LMI를 이용한 풀이를 이용한다. 그리고 간단한 예제를 통하여 그 성능을 입증한다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.6
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• pp.667-673
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• 2010

Recently, structures are becoming longer and higher because of the developments of new materials and construction techniques. However, such modern structures are more susceptible to excessive structural vibrations which cause deterioration in serviceability and structural safety. A modified probabilistic neural network(MPNN) approach is proposed to reduce the structural vibration. In this study, the global probability density function(PDF) of MPNN is reflected by summing the heterogeneous local PDFs automatically determined in the individual standard deviation of each variable. The proposed algorithm is applied for the vibration control of a three-story shear building model under Northridge earthquake. When the control results of the MPNN are compared with those of conventional PNN to verify the control performance, the MPNN controller proves to be more effective than PNN methods in decreasing the structural responses.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.4
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• pp.551-558
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• 1998

In this paper, a job shop scheduling system is developed which can cope with the changes of shop floor status with flexibility. This system suggests near optimal sequence of operations by using Genetic Algorithm which considers alternative process plans. The Genetic Algorithm proposed in this paper has some characteristics. The mutation rate is differentiated in order to enhance the chance to escape a local optimum and to assure the global optimum. And it employs the double gene structure to easily make the modeling of the shop floor. Finally, the quality of its solution and the computational time are examined in comparison with the method of a Simulated Annealing.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.39
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• pp.1-8
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• 1996

본 연구에서는 공정계획과 일정계획을 순차적으로 수행하는 기존의 방법과는 달리, 공정계획의 선정과 일정계획의 동시적 접근을 통하여 생산시스템의 효율을 향상시키기 위한 통합방법론을 제시하고자 한다. 공정계획과 일정계획기의 순차적 접근방법에서는 공정계획과 일정계획이 각각 지역적 판단근거(local criteria)에 의해 순차적으로 선정되어 생산 시스템의 전역적 판단근거(global criteria)와 상충(conflicts)되는 경우가 자주 발생하여 시스템의 폭주(congestion)나 새 계획 등의 원인이 되고 있다. 이와 같은 문제점들을 극복하기 위해 본 연구에서는 통합적 접근을 통해 전역적 판단근거에 의한 공정계획과 일정계획의 동시접근방법을 제시하고 한다.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.1
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• pp.37-48
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• 2022

In this study, a hybrid meta-heuristic approach is proposed for solving engineering design optimization problems. Various approaches in many literatures have been proposed to solve engineering optimization problems with various types of decision variables and complex constraints. Unfortunately, however, their efficiencies for locating optimal solution do not be highly improved. Therefore, we propose a hybrid meta-heuristic approach for improving their weaknesses. the proposed GA-VNS-HC approach is combining genetic algorithm (GA) for global search with variable neighborhood search (VNS) and hill climbing (HC) for local search. In case study, various types of engineering design optimization problems are used for proving the efficiency of the proposed GA-VNS-HC approach