• Title/Summary/Keyword: Parameter optimization

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OPTIMAL FORMATION TRAJECTORY-PLANNING USING PARAMETER OPTIMIZATION TECHNIQUE

  • Lim, Hyung-Chul;Bang, Hyo-Choong;Park, Kwan-Dong;Lee, Woo-Kyoung
    • Journal of Astronomy and Space Sciences
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    • v.21 no.3
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    • pp.209-220
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    • 2004
  • Some methods have been presented to get optimal formation trajectories in the step of configuration or reconfiguration, which subject to constraints of collision avoidance and final configuration. In this study, a method for optimal formation trajectory-planning is introduced in view of fuel/time minimization using parameter optimization technique which has not been applied to optimal trajectory-planning for satellite formation flying. New constraints of nonlinear equality are derived for final configuration and constraints of nonlinear inequality are used for collision avoidance. The final configuration constraints are that three or more satellites should be placed in an equilateral polygon of the circular horizontal plane orbit. Several examples are given to get optimal trajectories based on the parameter optimization problem which subjects to constraints of collision avoidance and final configuration. They show that the introduced method for trajectory-planning is well suited to trajectory design problems of formation flying missions.

The Research on the Modeling and Parameter Optimization of the EV Battery (전기자동차 배터리 모델링 및 파라미터 최적화 기법 연구)

  • Kim, Il-Song
    • The Transactions of the Korean Institute of Power Electronics
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    • v.25 no.3
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    • pp.227-234
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    • 2020
  • This paper presents the methods for the modeling and parameter optimization of the electric vehicle battery. The state variables of the battery are defined, and the test methods for battery parameters are presented. The state-space equation, which consists of four state variables, and the output equation, which is a combination of to-be-determined parameters, are shown. The parameter optimization method is the key point of this study. The least square of the modeling error can be used as an initial value of the multivariable function. It is equivalent to find the minimum value of the error function to obtain optimal parameters from multivariable function. The SIMULINK model is presented, and the 10-hour full operational range test results are shown to verify the performance of the model. The modeling error for 25 degrees is approximately 1% for full operational ranges. The comments to enhance modeling accuracy are shown in the conclusion.

Torque Ripple Minimization of PMSM Using Parameter Optimization Based Iterative Learning Control

  • Xia, Changliang;Deng, Weitao;Shi, Tingna;Yan, Yan
    • Journal of Electrical Engineering and Technology
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    • v.11 no.2
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    • pp.425-436
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    • 2016
  • In this paper, a parameter optimization based iterative learning control strategy is presented for permanent magnet synchronous motor control. This paper analyzes the mechanism of iterative learning control suppressing PMSM torque ripple and discusses the impact of controller parameters on steady-state and dynamic performance of the system. Based on the analysis, an optimization problem is constructed, and the expression of the optimal controller parameter is obtained to adjust the controller parameter online. Experimental research is carried out on a 5.2kW PMSM. The results show that the parameter optimization based iterative learning control proposed in this paper achieves lower torque ripple during steady-state operation and short regulating time of dynamic response, thus satisfying the demands for both steady state and dynamic performance of the speed regulating system.

Supervised Learning Artificial Neural Network Parameter Optimization and Activation Function Basic Training Method using Spreadsheets (스프레드시트를 활용한 지도학습 인공신경망 매개변수 최적화와 활성화함수 기초교육방법)

  • Hur, Kyeong
    • Journal of Practical Engineering Education
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    • v.13 no.2
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    • pp.233-242
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    • 2021
  • In this paper, as a liberal arts course for non-majors, we proposed a supervised learning artificial neural network parameter optimization method and a basic education method for activation function to design a basic artificial neural network subject curriculum. For this, a method of finding a parameter optimization solution in a spreadsheet without programming was applied. Through this training method, you can focus on the basic principles of artificial neural network operation and implementation. And, it is possible to increase the interest and educational effect of non-majors through the visualized data of the spreadsheet. The proposed contents consisted of artificial neurons with sigmoid and ReLU activation functions, supervised learning data generation, supervised learning artificial neural network configuration and parameter optimization, supervised learning artificial neural network implementation and performance analysis using spreadsheets, and education satisfaction analysis. In this paper, considering the optimization of negative parameters for the sigmoid neural network and the ReLU neuron artificial neural network, we propose a training method for the four performance analysis results on the parameter optimization of the artificial neural network, and conduct a training satisfaction analysis.

Modified complex mode superposition design response spectrum method and parameters optimization for linear seismic base-isolation structures

  • Huang, Dong-Mei;Ren, Wei-Xin;Mao, Yun
    • Earthquakes and Structures
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    • v.4 no.4
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    • pp.341-363
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    • 2013
  • Earthquake response calculation, parametric analysis and seismic parameter optimization of base-isolated structures are some critical issues for seismic design of base-isolated structures. To calculate the earthquake responses for such non-symmetric and non-classical damping linear systems and to implement the earthquake resistant design codes, a modified complex mode superposition design response spectrum method is put forward. Furthermore, to do parameter optimization for base-isolation structures, a graphical approach is proposed by analyzing the relationship between the base shear ratio of a seismic base-isolation floor to non-seismic base-isolation one and frequency ratio-damping ratio, as well as the relationship between the seismic base-isolation floor displacement and frequency ratio-damping ratio. In addition, the influences of mode number and site classification on the seismic base-isolation structure and corresponding optimum parameters are investigated. It is demonstrated that the modified complex mode superposition design response spectrum method is more precise and more convenient to engineering applications for utilizing the damping reduction factors and the design response spectrum, and the proposed graphical approach for parameter optimization of seismic base-isolation structures is compendious and feasible.

A Study on the Parameter Optimization of Inverter for Induction Heating Cooking Appliance (유도가열 조리기기용 인버터 파라미터 최적화에 관한 연구)

  • Kang, Byung-Kwan;Lee, Se-Min;Park, Jung-Wook
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.1
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    • pp.77-85
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    • 2009
  • With the advent of power semiconductor switching devices, power electronics relating to high frequency electromagnetic eddy current based induction heating technology have become more suitable and acceptable. This paper presents high-frequency induction heating cooking appliance circuit based on the zero current switching-PWM single ended push-pull(ZCS-PWM SEPP) resonant inverter added AC-DC converter. This inverter uses pulse-width-modulation(PWM) control method with active auxiliary quasi-resonant lossless inductor snubbers and a switched capacitor. To improved the transient performance, the PI controller is applied for this system. For the systematic parameter optimization of the PI controller, the gradient-based optimization algorithm is applied. The performance of optimized parameters is evaluated using simulation and experimental test. These results show that the proposed systematic optimal tuning method improve the transient performances of this system.

Finite Element Analysis and Geometric Parameter Optimization for BMT Driving Assembly (BMT 구동장치의 유한요소해석 및 형상변수 최적화)

  • Park, Young-Whan;Kwak, Jae-Seob;Jiating, Yan
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.19 no.2
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    • pp.178-183
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    • 2010
  • Base-mounted type(BMT) driving assembly in CNC machine tools is an indispensable part to improve productivity by reducing tool changeover time and to meet the ever-increasing demand of precision machine tools. This study aimed to perform finite element analysis and geometric parameter optimization to improve the efficiency of BMT driving assembly. First, simulations for three-dimensional structural and vibration analysis were performed using ANSYS/Workbench on the initial geometric models of BMT driving assembly. After analyzing stress and deformation concentration zones, several new geometrical models were designed and evaluated by design of experiments and ANSYS/DesignXplorer. Through a series of analysis-evaluation-modification cycles, it was seen that designed models were effective in determining optimal geometry of BMT driving assembly.

A New Approach to Adaptive HFC-based GAs: Comparative Study on Crossover Genetic Operator (적응 HFC 기반 유전자알고리즘의 새로운 접근: 교배 유전자 연산자의 비교연구)

  • Kim, Gil-Sung;Choi, Jeoung-Nae;Oh, Sung-Kwun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.9
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    • pp.1636-1641
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    • 2008
  • In this study, we introduce a new approach to Parallel Genetic Algorithms (PGA) which combines AHFCGA with crossover operator. As to crossover operators, we use three types of the crossover operators such as modified simple crossover(MSX), arithmetic crossover(AX), and Unimodal Normal Distribution Crossover(UNDX) for real coding. The AHFC model is given as an extended and adaptive version of HFC for parameter optimization. The migration topology of AHFC is composed of sub-populations(demes), the admission threshold levels, and admission buffer for the deme of each threshold level through succesive evolution process. In particular, UNDX is mean-centric crossover operator using multiple parents, and generates offsprings obeying a normal distribution around the center of parents. By using test functions having multimodality and/or epistasis, which are commonly used in the study of function parameter optimization, Experimental results show that AHFCGA can produce more preferable output performance result when compared to HFCGA and RCGA.

A Transmission Parameter Optimization Scheme Based on Genetic Algorithm for Dynamic Spectrum Access (동적 스펙트럼 접근을 위한 유전자 알고리즘 기반 전송 매개변수 최적화 기법)

  • Chae, Keunhong;Yoon, Seokho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38A no.11
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    • pp.938-943
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    • 2013
  • In this paper, we propose a transmission parameter optimization scheme based on genetic algorithm for dynamic spectrum access systems. Specifically, we represent a multiple objective fitness function as a weighted sum of single objective fitness functions to optimize transmission parameters, and then, obtain optimized transmission parameters based on genetic algorithm for given transmission scenarios. From numerical results, we confirm that the transmission parameters are well optimized by using the proposed optimization scheme.

Comparison of Hyper-Parameter Optimization Methods for Deep Neural Networks

  • Kim, Ho-Chan;Kang, Min-Jae
    • Journal of IKEEE
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    • v.24 no.4
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    • pp.969-974
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    • 2020
  • Research into hyper parameter optimization (HPO) has recently revived with interest in models containing many hyper parameters, such as deep neural networks. In this paper, we introduce the most widely used HPO methods, such as grid search, random search, and Bayesian optimization, and investigate their characteristics through experiments. The MNIST data set is used to compare results in experiments to find the best method that can be used to achieve higher accuracy in a relatively short time simulation. The learning rate and weight decay have been chosen for this experiment because these are the commonly used parameters in this kind of experiment.