• Structural Engineering and Mechanics
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• 제37권5호
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• pp.475-487
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• 2011

In a flexible multi-body dynamic system the typical topological optimization method for structures cannot be directly applied, as the stiffness varies with position. In this paper, the topological optimization of the flexible multi-body dynamic system is converted into structural optimization using the equivalent static load method. First, the actual boundary conditions of the control system and the approximate stiffness curve of the mechanism are obtained from a flexible multi-body dynamical simulation. Second, the finite element models are built using the absolute nodal coordination for different positions according to the stiffness curve. For efficiency, the static reanalysis method is utilized to solve these finite element equilibrium equations. Specifically, the finite element equilibrium equations of key points in the stiffness curve are fully solved as the initial solution, and the following equilibrium equations are solved using a reanalysis method with an error controlled epsilon algorithm. In order to identify the efficiency of the elements, a non-dimensional measurement is introduced. Finally, an improved evolutional structural optimization (ESO) method is used to solve the optimization problem. The presented method is applied to the optimal design of a die bonder. The numerical results show that the presented method is practical and efficient when optimizing the design of the mechanism.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2001년도 Proceedings ICPE 01 2001 International Conference on Power Electronics
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• pp.428-433
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• 2001

This paper presents the control algorithm for maximum efficiency drives of an induction motor system with the high dynamic performance. This system uses a simple model of the induction motor that includes equations of iron losses. The model, which only requires the parameters of induction motor, is referred to a field-oriented frame. The minimum point of the input power can be obtained at the steady state condition. The reference torque and flux currents for the vector control of induction motors are calculated by the optimal efficiency control algorithm. The drive system with the proposed efficiency optimization controller has been implemented by a 32 bit floating point TMS320C32 DSP chip. The results show the effectiveness of the control strategy proposed for the induction motor drive.

• Journal of Power Electronics
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• 제18권5호
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• pp.1595-1607
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• 2018

In this paper, a hierarchical control strategy is introduced to control a new three-port multidirectional DC-DC converter for integrating an energy storage system (ESS) to a bipolar DC microgrid (BPDCMG). The proposed converter provides a voltage-balancing function for the BPDCMG and adjusts the states of charge (SoC) of the ESS. Previous studies tend to balance the voltage of the BPDCMG buses with active sources or by transferring power from one bus to another. Furthermore, the batteries available in BPDCMGs were charged equally by both buses. However, this power sharing method does not guarantee efficient operation of the whole system. In order to achieve a higher efficiency and lower energy losses, a triple-layer hierarchical control strategy, including a primary droop controller, a secondary voltage restoration controller and a tertiary optimization controller are proposed. Thanks to the multi-functional operation of the proposed converter, its conversion stages are reduced. Furthermore, the efficiency and weight of the system are both improved. Therefore, this converter has a significant capability to be used in portable BPDCMGs such as electric DC ships. The converter modes are analyzed and small-signal models of the converter are extracted. Comprehensive simulation studies are carried out and a BPDCMG laboratory setup is implemented in order to validate the effectiveness of the proposed converter and its hierarchical control strategy. Simulation and experimental results show that using the proposed converter mitigates voltage imbalances. As a result, the system efficiency is improved by using the hierarchical optimal power flow control.

• Journal of Computing Science and Engineering
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• 제8권1호
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• pp.1-10
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• 2014

The Bacterial Foraging Optimization Algorithm is a swarm intelligence optimization algorithm. This paper first analyzes the chemotaxis, as well as elimination and dispersal operation, based on the basic Bacterial Foraging Optimization Algorithm. The elimination and dispersal operation makes a bacterium which has found or nearly found an optimal position escape away from that position, which greatly affects the convergence speed of the algorithm. In order to avoid this escape, the sphere of action of the elimination and dispersal operation can be altered in accordance with the generations of evolution. Secondly, we put forward an algorithm of an adaptive adjustment of step length we called improved bacterial foraging optimization (IBFO) after making a detailed analysis of the impacts of the step length on the efficiency and accuracy of the algorithm, based on chemotaxis operation. The classic test functions show that the convergence speed and accuracy of the IBFO algorithm is much better than the original algorithm.

• 한국식품과학회지
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• 제24권5호
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• pp.428-439
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• 1992

고추건조에 대한 에너지사용의 효율성을 표현할 수 있는 건조효율 지표를 유도하고 정의하였으며 건조효율에 미치는 공정변수의 영향을 분석하고 carotenoids 보존의 제한조건하에서 건조효율을 최대화시키는 최적건조조건을 찾았다. 전체 사용에너지에 대한 증발에너지의 비로 단순화시켜서 열풍의 건구 및 습구온도의 함수로 표현된 건조효율이 건조공정중 실제의 에너지 사용의 효율성을 표현할 수 있는 것으로 확인되었고, 이를 이용하여 주어진 조건에서의 최적화가 가능하였다. 최적화 결과 1단계 건조에 비해서 2단계 건조가 같은 품질제한 조건하에서 건조효율을 증가시킬 수 있었다. 한편 배기공기 온도를 포함하는 간단한 변환변수와 건조되는 고추의 수분함량 사이의 관계에 의하여 건조시간 종료를 제어할 수 있는 가능성도 검토되었다. 전체적으로 본 연구에서 고추 건조시 좋은 품질을 유지하면서 건조효율을 향상시키고 에너지소비를 절감할 수 있는 건조기 운전의 방향을 제시하였다.

• Journal of Magnetics
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• 제21권4호
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• pp.586-592
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• 2016

The magnetic-jack type CRDM withdraws or inserts a control rod assembly from/to the reactor core to control the core reactivity. The CRDM housings form not only the path of the electromagnetic field but also the pressure boundary of a nuclear reactor, and a periodic in-service inspection should be carried out if there are welded or flange jointed parts on the pressure boundary. The in-service inspection is a time-consuming process during the reactor refueling, and moreover it is difficult to perform the inspection over the reactor head. A magnetic motor housing is applied for the current SMART CRDM and has several welding joints, however a nonmagnetic motor housing with fewer or no welding joints may improve the operational efficiency of the nuclear reactor by avoiding or simplifying the in-service inspection process. Prior to the development, the magnetic field transfer efficiency of the nonmagnetic housing was required to be assessed. It was verified and optimized by the electromagnetic analysis of the lifting force estimation. Magnetic flux rings were adopted to improve the efficiency. In this paper, the design and optimization process of a nonmagnetic motor housing with the magnetic flux rings for the SMART CRDM are introduced and the analyses results are discussed.

• ETRI Journal
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• 제42권4호
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• pp.505-517
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• 2020

The increasing size and complexity of deep neural networks (DNNs) necessitate the development of efficient high-performance accelerators. An efficient memory structure and operating scheme provide an intuitive solution for high-performance accelerators along with dataflow control. Furthermore, the processing of various neural networks (NNs) requires a flexible memory architecture, programmable control scheme, and automated optimizations. We first propose an efficient architecture with flexibility while operating at a high frequency despite the large memory and PE-array sizes. We then improve the efficiency and usability of our architecture by automating the optimization algorithm. The experimental results show that the architecture increases the data reuse; a diagonal write path improves the performance by 1.44× on average across a wide range of NNs. The automated optimizations significantly enhance the performance from 3.8× to 14.79× and further provide usability. Therefore, automating the optimization as well as designing an efficient architecture is critical to realizing high-performance DNN accelerators.

• 한국시뮬레이션학회논문지
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• 제5권1호
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• pp.91-106
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• 1996

Control Variate (CV) is very useful technique for variance reduction in a wide class of queueing network simulations. However, the loss in variance reduction caused by the estimation of the optimum control coefficients is an increasing function of the number of control variables. Therefore, in some situations, it is required to select an optimal set of control variables to maximize the variance reduction . In this paper, we develop the Adaptive Control Variates (ACV) method which selects an optimal set of control variates during the simulation adatively. ACV is useful to maximize the simulation efficiency when we need iterated simulations to find an optimal solution. One such an example is the Simulated Annealing (SA) because, in SA algorithm, we have to repeat in calculating the objective function values at each temperature, The ACV can also be applied to the queueing network optimization problems to find an optimal input parameters (such as service rates) to maximize the throughput rate with a certain cost constraint.

• 한국자동차공학회논문집
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• 제23권6호
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• pp.591-600
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• 2015

The efficiency of a powertrain system of hybrid vehicle is highly dependent on the design and control of the hybrid powertrain system. In other words, the optimal design of the powertrain systems is coupled with optimal control of the powertrain system. Therefore, the solution of an optimal design problem for hybrid vehicles is computationally and timely very expensive. For example, dynamic programming, which is a recursive optimization method, is usually used to evaluate the best fuel economy of certain hybrid vehicle design, and, thus, the evaluation takes tens of minutes to several hours. This research aims to accelerate the speed of efficiency evaluation of hybrid vehicles. We suggest a mathematical treat and a methodological treat to reduce the computational load. The mathematical treat is that the dynamics of system is discretized with sparse sampling time without loss of energy balance. The methodological treat is that the efficiency of the hybrid vehicle is inferred by characteristic loss evaluation that is computationally inexpensive. With the suggested methodology, evaluating a design candidate of hybrid powertrain system is taken few minutes, which was taken several hours when dynamic programming is used.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권12호
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• pp.5328-5346
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• 2016

An optimal power control algorithm based on convex optimization is proposed for base stations in long term evolution networks. An objective function was formulated to maximize the proportional fairness of the networks. The optimal value of the objective function was obtained using convex optimization and distributed methods based on the path loss model between the base station and users. Field tests on live networks were conducted to evaluate the performance of the proposed algorithm. The experimental results verified that, in a multi-cell multi-user scenario, the proposed algorithm increases system throughputs, proportional fairness, and energy efficiency by 9, 1.31 and 20.2 %, respectively, compared to the conventional fixed power allocation method.