• Journal of Communications and Networks
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• 제13권5호
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• pp.472-480
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• 2011

In this paper, we investigate two new candidate transmission schemes, non-orthogonal frequency reuse (NOFR) and beam-hopping (BH). They operate in different domains (frequency and time/space, respectively), and we want to know which domain shows overall best performance. We propose a novel formulation of the signal-to-interference plus noise ratio (SINR) which allows us to prove the frequency/time duality of these schemes. Further, we propose two novel capacity optimization approaches assuming per-beam SINR constraints in order to use the satellite resources (e.g., power and bandwidth) more efficiently. Moreover, we develop a general methodology to include technological constraints due to realistic implementations, and obtain the main factors that prevent the two technologies dual of each other in practice, and formulate the technological gap between them. The Shannon capacity (upper bound) and current state-of-the-art coding and modulations are analyzed in order to quantify the gap and to evaluate the performance of the two candidate schemes. Simulation results show significant improvements in terms of power gain, spectral efficiency and traffic matching ratio when comparing with conventional systems, which are designed based on uniform bandwidth and power allocation. The results also show that BH system turns out to show a less complex design and performs better than NOFR system specially for non-real time services.

• 한국인터넷방송통신학회논문지
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• 제16권4호
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• pp.89-96
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• 2016

본 논문에서는 데이터수집을 위한 MDC(mobile data collector) 기반의 무선센서네트워크를 고려한다. 이러한 네트워크에서는 MDC들이 이동하며 주위환경으로부터 데이터를 수집한 후 싱크노드에게 전달한다. 단일 MDC를 사용하는 기존 방식에서는 높은 데이터 수집 지연 문제가 발생한다. 복수의 MDC를 사용하는 일부 기존 방안에서는 네트워크 수명최대화에 초점을 두고 데이터 전달 지연에 대한 고려는 하지 않았다. 기존 방안의 이러한 제약을 극복하기 위하여 본 논문에서는 MDC의 개수가 주어진 상황에서 패킷지연을 최소화하는 문제와, 최대 허용 패킷 지연이 주어진 상황에서 필요한 MDC의 수를 최소화 하는 문제를 고려한다. 이를 위해서 두 개의 최적화 문제가 구성되었으며 MDC들의 이동거리와 이동시간 추정 모델을 개발하였다. Interior-point 알고리즘을 이용하여 최적화 문제에 대한 해를 구했으며, 제안된 방안을 검증하기 위한 수치결과와 분석을 제시하였다.

• 로봇학회논문지
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• 제15권3호
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• pp.212-220
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• 2020

This paper deals with a strategy of gain optimization for the kinematic control algorithm of a wire-driven surgical robot. The proposed controller consists of the closed-loop inverse kinematics with the back-calculation method. The closed-loop inverse kinematics has 18 PID control gains, and the back-calculation method has 6 gains. An efficient strategy is designed to optimize 18 values first and then the remaining 6 values. The optimal gain sets are searched under the step input with performance indices. In this gain optimization, the objective function is defined as the minimum value of signal-to-noise ratio of the performance indices for 6 DoF (Degree-of-Freedom) motion that is based on the Taguchi method, and the constraints are applied to obtain stable responses for each motion evenly. The gain sets obtained are verified by simulations using the test trajectories. In comparative results, the optimal gain value based on the performance index combined with ISE (integral of square error) and settling time showed the best control performance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.333-336
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• 1991

In this paper, Hopfield & Tank model-like artificial neural network structure is proposed, which can be used for the optimal path planning problems such as the unit commitment problems or the maintenance scheduling problems which have been solved by the dynamic programming method or the branch and bound method. To construct the structure of the neural network, an energy function is defined, of which the global minimum means the optimal path of the problem. To avoid falling into one of the local minima during the optimization process, the simulated annealing method is applied via making the slope of the sigmoid transfer functions steeper gradually while the process progresses. As a result, computer(IBM 386-AT 34MHz) simulations can finish the optimal unit commitment problem with 10 power units and 24 hour periods (1 hour factor) in 5 minites. Furthermore, if the full parallel neural network hardware is contructed, the optimization time will be reduced remarkably.

• 한국경영과학회지
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• 제25권1호
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• pp.27-36
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• 2000

We perform a computational complexity analysis of a heuristic algotithm proposed in the literature for the combinatorial optimization problems extended with a single side-constraint. This algorithm, although such a view was not given in the original work, is a disguised version of an optimal Lagrangian dual solution technique. It also has been observed to be a very efficient heuristic producing near-optimal solutions for the primal problems in some experiments. Especially, the number of iterations grows sublinearly in terms of the network node size so that the heuristic seems to be particularly suitable for the applicatons such as routing with semi-real time requirements. The goal of this paper is to establish a polynomal worst-case complexity of the algorithm. In particular, the obtained complexity bound suports the sublinear growth of the required iterations.

• 전기학회논문지
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• 제57권8호
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• pp.1429-1433
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• 2008

In this paper, we consider the design method of robust guaranteed cost controller for discrete-time singular systems with norm-bounded time-varying parameter uncertainty. In order to get the optimum(minimum) value of guaranteed cost, an optimization problem is given by linear matrix inequality (LMI) approach. The sufficient condition for the existence of controller and the upper bound of guaranteed cost function are proposed in terms of strict LMIs without decompositions of system matrices. Numerical examples are provided to show the validity of the presented method.

• International Journal of Automotive Technology
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• 제6권1호
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• pp.71-77
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• 2005

This paper presents a systematic approach which determines the optimal period to minimize performance measure subject to the schedulability constraints of a real-time control system by formulating the scheduling problem as an optimal problem. The performance measure is derived from the summation of end-to-end response times of processed I/Os scheduled by the static cyclic method. The schedulability constraint is specified in terms of allowable resource utilization. At first, a uniprocessor case is considered and then it is extended to a distributed system connected through a communication link, local-inter network, UN. This approach is applied to the design of an automotive body control system in order to validate the feasibility through a real example. By using the approach, a set of optimal periods can easily be obtained without complex and advanced methods such as branch and bound (B&B) or simulated annealing.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 하계종합학술대회 논문집(2)
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• pp.459-462
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• 2004

In this paper, we present a reducing power consumption of a scheduling for module selection under the time constraint. A a reducing power consumption of a scheduling for module selection under the time constraint execute scheduling and allocation for considering the switching activity. The focus scheduling of this phase adopt Force-Directed Scheduling for low power to existed Force-Directed Scheduling. and it constructs the module selection RT library by in account consideration the mutual correlation of parameters in which the power and the area and delay. when it is, in this paper we formulate the module selection method as a multi-objective optimization and propose a branch and bound approach to explore the large design space of module selection. Therefore, the optimal module selection method proposed to consider power, area, delay parameter at the same time. The comparison experiment analyzed a point of difference between the existed FDS algorithm and a new FDS_RPC algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.702-704
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• 2004

This paper focuses on the problem of asymptotic stabilization for uncertain time-delay systems with saturating actuator. We propose a state feedback controller which maximizes the delay bound for guaranteeing stability of the system. Then, based on the Lyapunov method, a delay-dependent stabilization criterion is devised by taking the relationship between the terms in the Leibniz-Newton formula into account. The criterion is represented in terms of LMIs, which can be solved by various efficient convex optimization algorithm. Numerical examples are given to illustrate our main method.

• 전기학회논문지
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• 제57권3호
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• pp.458-465
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• 2008

In this paper, we propose a non-fragile guaranteed cost controller design method for uncertain linear systems with constant delyas in state. The norm bounded and time-varying uncertainties are subjected to system and controller design matrices. A quadratic cost function is considered as the performance measure for the system. Based on the Lyapunov method, an LMI(Linear Matrix Inequality) optimization problem is established to design the controller which uses information of delayed state and minimizes the upper bound of the quadratic cost function for all admissible system uncertainties and controller gain variations. Numerical examples show the effectiveness of the proposed method.