• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권1호
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• pp.188-210
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• 2022

As a promising technique to support tremendous numbers of Internet of Things devices and a variety of applications efficiently, mobile edge computing (MEC) has attracted extensive studies recently. In this paper, we consider a MEC-assisted peer-to-peer (P2P) mobile communication system where MEC servers are deployed at access points to accelerate the communication process between mobile terminals. To capture the tradeoff between the time delay and the energy consumption of the system, a cost function is introduced to facilitate the optimization of the computation and communication resources. The formulated optimization problem is non-convex and is tackled by an iterative block coordinate descent algorithm that decouples the original optimization problem into two subproblems and alternately optimizes the computation and communication resources. Moreover, the MEC-assisted P2P communication system is compared with the conventional P2P communication system, then a condition is provided in closed-form expression when the MEC-assisted P2P communication system performs better. Simulation results show that the advantage of this system is enhanced when the computing capability of the receiver increases whereas it is reduced when the computing capability of the transmitter increases. In addition, the performance of this system is significantly improved when the signal-to-noise ratio of hop-1 exceeds that of hop-2.

• Smart Structures and Systems
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• 제31권3호
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• pp.247-257
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• 2023

In structural health monitoring of large-scale structures, optimal sensor placement plays an important role because of the high cost of sensors and their supporting instruments, as well as the burden of data transmission and storage. In this study, a vibration sensor placement algorithm based on deep reinforcement learning (DRL) is proposed, which can effectively solve non-convex, high-dimensional, and discrete combinatorial sensor placement optimization problems. An objective function is constructed to estimate the quality of a specific vibration sensor placement scheme according to the modal assurance criterion (MAC). Using this objective function, a DRL-based algorithm is presented to determine the optimal vibration sensor placement scheme. Subsequently, we transform the sensor optimal placement process into a Markov decision process and employ a DRL-based optimization algorithm to maximize the objective function for optimal sensor placement. To illustrate the applicability of the proposed method, two examples are presented: a 10-story braced frame and a sea-crossing bridge model. A comparison study is also performed with a genetic algorithm and particle swarm algorithm. The proposed DRL-based algorithm can effectively solve the discrete combinatorial optimization problem for vibration sensor placements and can produce superior performance compared with the other two existing methods.

• Journal of Communications and Networks
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• 제16권1호
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• pp.36-44
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• 2014

Exploiting the energy-delay tradeoff for energy saving is critical for developing green wireless communication systems. In this paper, we investigate the delay-constrained energy-efficient packet transmission. We aim to minimize the energy consumption of multiple randomly arrived packets in an additive white Gaussian noise channel subject to individual packet delay constraints, by taking into account the practical on-off circuit power consumption at the transmitter. First, we consider the offline case, by assuming that the full packet arrival information is known a priori at the transmitter, and formulate the energy minimization problem as a non-convex optimization problem. By exploiting the specific problem structure, we propose an efficient scheduling algorithm to obtain the globally optimal solution. It is shown that the optimal solution consists of two types of scheduling intervals, namely "selected-off" and "always-on" intervals, which correspond to bits-per-joule energy efficiency maximization and "lazy scheduling" rate allocation, respectively. Next, we consider the practical online case where only causal packet arrival information is available. Inspired by the optimal offline solution, we propose a new online scheme. It is shown by simulations that the proposed online scheme has a comparable performance with the optimal offline one and outperforms the design without considering on-off circuit power as well as the other heuristically designed online schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권4호
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• pp.1837-1860
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• 2020

We propose a general framework for studying resource allocation problem and the tradeoff between spectral efficiency (SE) and energy efficiency (EE) for downlink traffic in power domain-non-orthogonal multiple access (PD-NOMA) and device to device (D2D) based heterogeneous cloud radio access networks (H-CRANs) under imperfect channel state information (CSI). The aim is jointly optimize radio remote head (RRH) selection, spectrum allocation and power control, which is formulated as a multi-objective optimization (MOO) problem that can be solved with weighted Tchebycheff method. We propose a low-complexity algorithm to solve user association, spectrum allocation and power coordination separately. We first compute the CSI for RRHs. Then we study allocating the cell users (CUs) and D2D groups to different subchannels by constructing a bipartite graph and Hungrarian algorithm. To solve the power control and EE-SE tradeoff problems, we decompose the target function into two subproblems. Then, we utilize successive convex program approach to lower the computational complexity. Moreover, we use Lagrangian method and KKT conditions to find the global optimum with low complexity, and get a fast convergence by subgradient method. Numerical simulation results demonstrate that by using PD-NOMA technique and H-CRAN with D2D communications, the system gets good EE-SE tradeoff performance.

• Structural Engineering and Mechanics
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• 제29권5호
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• pp.489-504
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• 2008

In piezoelectric flexible structures, the contribution of vibration modes to the dynamic response of system may change with the location of piezoelectric actuator patches, which means that the ability of actuators to control vibration modes should be taken into account in the development of modal reduction model. The spatial $H_2$ norm of modes, which serves as a measure of the intensity of modes to system dynamical response, is used to pick up the modes included in the reduction model. Based on the reduction model, the paper develops the state-space representation for uncertain flexible tructures with piezoelectric material as non-collocated actuators/sensors in the modal space, taking into account uncertainties due to modal parameters variation and unmodeled residual modes. In order to suppress the vibration of the structure, a dynamic output feedback control law is designed by imultaneously considering the conflicting performance specifications, such as robust stability, transient response requirement, disturbance rejection, actuator saturation constraints. Based on linear matrix inequality, the vibration control design is converted into a linear convex optimization problem. The simulation results show how the influence of vibration modes on the dynamical response of structure varies with the location of piezoelectric actuators, why the uncertainties should be considered in the reductiom model to avoid exciting high-frequency modes in the non-collcated vibration control, and the possiblity that the conflicting performance specifications are dealt with simultaneously.

• International Journal of Control, Automation, and Systems
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• 제6권1호
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• pp.24-34
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• 2008

A novel neural network model, termed the standard neural network model (SNNM), similar to the nominal model in linear robust control theory, is suggested to facilitate the synthesis of controllers for delayed (or non-delayed) nonlinear systems composed of neural networks. The model is composed of a linear dynamic system and a bounded static delayed (or non-delayed) nonlinear operator. Based on the global asymptotic stability analysis of SNNMs, Static state-feedback controller and dynamic output feedback controller are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based nonlinear systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Two application examples are given where the SNNMs are employed to synthesize the feedback stabilizing controllers for an SISO nonlinear system modeled by the neural network, and for a chaotic neural network, respectively. Through these examples, it is demonstrated that the SNNM not only makes controller synthesis of neural-network-based systems much easier, but also provides a new approach to the synthesis of the controllers for the other type of nonlinear systems.

• 전자공학회논문지SC
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• 제44권1호
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• pp.59-66
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• 2007

본 논문은 변수 불확실성과 제어기의 곱셈형 섭동을 가지는 특이시스템에 대한 비약성 강인 보장비용 제어기 설계 알고리듬을 제안한다. 제어기가 존재할 조건, 비약성 보장비용 제어기 설계 방법, 제어기에서의 비약성 척도와 보장비용 성능지수를 최소화하는 보장비용의 상한치(upper bound)를 선형행렬부등식 접근방벙으로 제안한다. 또한, 특이치분해와 변수치환 및 슈어 여수정리를 이용하여 구한 충분조건은 구하고자 하는 변수의 견지에서 볼록최적화(convex optimization)가 가능한 선형행렬부등식으로 변형된다. 따라서, 제안한 비약성 강인 보장비용 제어기는 변수 불확실성과 제어기의 곱셈형 섭동을 가지는 폐루프 특시이스템의 점근적 안정성과 보장비용 성능지수를 최소화하고 제어기의 섭동에 대해서도 안정성을 보장한다. 마지막으로, 수치예제를 통하여 제안한 알고리듬의 타당성을 검증한다.

• 전자공학회논문지SC
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• 제42권6호
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• pp.9-14
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• 2005

본 논문은 특이시스템과 곱셈형 섭동을 가지는 제어기에 대한 비약성 $H_{\infty}$ 제어기 설계 알고리듬을 제안한다. 제어기가 존재할 조건과 비약성 $H_{\infty}$ 제어기 설계 방법 및 제어기에서의 비약성 척도를 선형행렬부등식 접근방법으로 제안한다. 또한, 특이치 분해와 변수치환 및 슈어 여수정리를 이용하여 구한 충분조건은 구하고자 하는 모든 변수의 견지에서 볼록최적화(convex optimization)가 가능한 하나의 선형행렬부등식으로 변형된다. 따라서, 제안한 비약성 $H_{\infty}$ 제어기는 점근적 안정성과 폐루프 특이시스템의 $H_{\infty}$ 노옴 유계 및 제어기의 곱셈형 섭동에 대한 안정성을 보장한다. 또한, 제안한 알고리듬을 이용하면 변수 불확실성을 가지는 특이시스템에 대한 강인 비약성 $H_{\infty}$ 제어기 설계 문제에도 쉽게 확장됨을 보인다. 마지막으로, 수치예제를 통하여 제안한 알고리듬의 타당성을 검증한다.

• 한국수자원학회논문집
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• 제52권10호
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• pp.681-695
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• 2019

Transient Stroage Model (TSM)은 하천을 본류대와 저장대로 나누어 각각에 대한 오염물의 혼합거동을 해석함으로써 복잡한 하천에 유입된 오염물질 혼합을 이해하는 데에 가장 많이 이용되는 모형 중 하나이다. TSM의 매개변수들은 역산모형을 통해 산정하게 되는데 이는 자연하천에서 추적자실험을 통해 계측된 농도곡선에 가장 잘 맞는 TSM 모의 농도곡선을 찾는 최적화 문제이다. 저장대모형의 매개변수 산정에 관한 선행 연구들에 의해 매개변수를 산정하는 최적화 문제의 비볼록(non-convex) 특성에서 오는 불확실성이 보고되어 왔다. 본 연구에서는 청미천에서 수행된 추적자실험으로부터 취득된 농도곡선을 이용해 최상의 최적화 기법과 목적함수의 조합에 대해 분석하였다. 최적화 문제의 수렴성과 수렴 속도를 모두 만족하는 최적화 조건을 결정하기 위해 SCE-UA의 CCE와 SP-UCI의 MCCE와 같은 진화 알고리즘 기반의 전역 최적화 방법들과 오차 기반 목적함수들을 Shuffled Complex-Self Adaptive Hybrid EvoLution (SC-SAHEL)을 활용해 비교하였다. 전반적인 변수 산정 결과 여러 EA를 동시에 적용한 SC-SAHEL을 평균 제곱오차를 목적함수로 한 방법이 가장 빠르고 가장 안정적으로 최적해에 수렴하는 것으로 나타났다.

• 전자공학회논문지C
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• 제36C권7호
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• pp.56-64
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• 1999

본 논문에서는 연속 어핀 Takagi-Sugeno 퍼지 시스템의 안정도를 판정하는 새로운 방법을 제안한다. 제안된 방법은 최근 각광을 받고 있는 선형 행렬 부등식이라는 컨벡스 최적화 기법을 이용하여 쉽게 구현할 수 있다. 우선 어핀 Takagi-Sugeno 퍼지 시스템이 안정하도록 되는 조건을 유도하고 이를 선형 행렬 부등식의 형태로 변형하고 수치적 접근방식을 제안한다. 끝으로 컴퓨터 모의 실험을 통하여 제안한 방법의 타당성을 확인한다.