• Title/Summary/Keyword: Parameters Optimization

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Optimization of Extended UNIQUAC Parameter for Activity Coefficients of Ions of an Electrolyte System using Genetic Algorithms

  • Hashemi, Seyed Hossein;Dehghani, Seyed Ali Mousavi;Khodadadi, Abdolhamid;Dinmohammad, Mahmood;Hosseini, Seyed Mohsen;Hashemi, Seyed Abdolrasoul
    • Korean Chemical Engineering Research
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    • v.55 no.5
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    • pp.652-659
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    • 2017
  • In the present research, in order to predict activity coefficient of inorganic ions in electrolyte solution of a petroleum system, we studied 13 components in the electrolyte solution, including $H_2O$, $CO_2$ (aq), $H^+$, $Na^+$, $Ba^{2+}$, $Ca^{2+}$, $Sr^{2+}$, $Mg^{2+}$, $SO_4$, $CO_3$, $OH^-$, $Cl^-$, and $HCO_3$. To predict the activity coefficient of the components of the petroleum system (a solid/liquid equilibrium system), activity coefficient model of Extended UNIQUAC was studied, along with its adjustable parameters optimized based on a genetic algorithm. The total calculated error associated with optimizing the adjustable parameters of Extended UNIQUAC model considering the 13 components under study at three temperature levels (298.15, 323.15, and 373.15 K) using the genetic algorithm is found to be 0.07.

3D Non-Rigid Registration for Abdominal PET-CT and MR Images Using Mutual Information and Independent Component Analysis

  • Lee, Hakjae;Chun, Jaehee;Lee, Kisung;Kim, Kyeong Min
    • IEIE Transactions on Smart Processing and Computing
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    • v.4 no.5
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    • pp.311-317
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    • 2015
  • The aim of this study is to develop a 3D registration algorithm for positron emission tomography/computed tomography (PET/CT) and magnetic resonance (MR) images acquired from independent PET/CT and MR imaging systems. Combined PET/CT images provide anatomic and functional information, and MR images have high resolution for soft tissue. With the registration technique, the strengths of each modality image can be combined to achieve higher performance in diagnosis and radiotherapy planning. The proposed method consists of two stages: normalized mutual information (NMI)-based global matching and independent component analysis (ICA)-based refinement. In global matching, the field of view of the CT and MR images are adjusted to the same size in the preprocessing step. Then, the target image is geometrically transformed, and the similarities between the two images are measured with NMI. The optimization step updates the transformation parameters to efficiently find the best matched parameter set. In the refinement stage, ICA planes from the windowed image slices are extracted and the similarity between the images is measured to determine the transformation parameters of the control points. B-spline. based freeform deformation is performed for the geometric transformation. The results show good agreement between PET/CT and MR images.

Design of the H Current Controller Based on the PSO Algorithm for Reducing the Current Ripple Caused by the Saliencies of SPMSM (SPMSM 인덕턴스 돌극성에 의한 전류리플 저감을 위한 PSO 알고리즘 기반의 H 전류 제어기 설계)

  • Lee, Kwan-Hyung;Young, Jeon-Chan;Lim, Dong-Jin
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.62 no.10
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    • pp.1425-1435
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    • 2013
  • The useful method for determining parameters of weighting functions used to design the $H_{\infty}$ current controller for attenuating the current ripple due to saliencies which SPMSM(Surface Permanent Magnet Synchronous Motor) also incorporates is described. To analyze the effect, the current ripple due to the structural and the saturation saliencies, the SPMSM model with nonlinear inductance function depending on the two independent variables, rotor position and stator current is simulated. After analysis, parameters of the weighting functions for $H_{\infty}$ current controller is selected to satisfy the robust stability, robust performance and specific performance in time and frequency domain by using the PSO(Particle Swarm Optimization) algorithm in the linear SPMSM model. Especially, the robust performance is proved that the selected weighting functions play a role in reducing the current ripple caused by the saliencies of SPMSM at the desired frequency range by the simple experiment.

A Six-Phase CRIM Driving CVT using Blend Modified Recurrent Gegenbauer OPNN Control

  • Lin, Chih-Hong
    • Journal of Power Electronics
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    • v.16 no.4
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    • pp.1438-1454
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    • 2016
  • Because the nonlinear and time-varying characteristics of continuously variable transmission (CVT) systems driven by means of a six-phase copper rotor induction motor (CRIM) are unconscious, the control performance obtained for classical linear controllers is disappointing, when compared to more complex, nonlinear control methods. A blend modified recurrent Gegenbauer orthogonal polynomial neural network (OPNN) control system which has the online learning capability to come back to a nonlinear time-varying system, was complied to overcome difficulty in the design of a linear controller for six-phase CRIM driving CVT systems with lumped nonlinear load disturbances. The blend modified recurrent Gegenbauer OPNN control system can carry out examiner control, modified recurrent Gegenbauer OPNN control, and reimbursed control. Additionally, the adaptation law of the online parameters in the modified recurrent Gegenbauer OPNN is established on the Lyapunov stability theorem. The use of an amended artificial bee colony (ABC) optimization technique brought about two optimal learning rates for the parameters, which helped reform convergence. Finally, a comparison of the experimental results of the present study with those of previous studies demonstrates the high control performance of the proposed control scheme.

Optimal Design for Flexible Passive Biped Walker Based on Chaotic Particle Swarm Optimization

  • Wu, Yao;Yao, Daojin;Xiao, Xiaohui
    • Journal of Electrical Engineering and Technology
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    • v.13 no.6
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    • pp.2493-2503
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    • 2018
  • Passive dynamic walking exhibits humanoid and energy efficient gaits. However, optimal design of passive walker at multi-variable level is not well studied yet. This paper presents a Chaotic Particle Swarm Optimization (CPSO) algorithm and applies it to the optimal design of flexible passive walker. Hip torsional stiffness and damping were incorporated into flexible biped walker, to imitate passive elastic mechanisms utilized in human locomotion. Hybrid dynamics were developed to model passive walking, and period-one gait was gained. The parameters global searching scopes were gained after investigating the influences of structural parameters on passive gait. CPSO were utilized to optimize the flexible passive walker. To improve the performance of PSO, multi-scroll Jerk chaotic system was used to generate pseudorandom sequences, and chaotic disturbance would be triggered if the swarm is trapped into local optimum. The effectiveness of CPSO is verified by comparisons with standard PSO and two typical chaotic PSO methods. Numerical simulations show that better fitness value of optimal design could be gained by CPSO presented. The proposed CPSO would be useful to design biped robot prototype.

Manipulator Joint Friction Identification using Genetic Algorithm and its Experimental Verification (유전 알고리듬을 이용한 매니퓰레이터 조인트의 마찰력 규명 및 실험적 검증)

  • Kim, Gyeong-Ho;Park, Yun-Sik
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.24 no.6 s.177
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    • pp.1633-1642
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    • 2000
  • Like many other mechanical dynamic systems, flexible manipulator systems experience stiction or sticking friction, which may cause input-dependent instabilities. Manipulator performance can be enha nced by identifying friction but it is hard and expensive to measure friction by direct and precise sensing of contact displacements and forces. This study addresses the problem of identifying flexible manipulator joint friction. A dynamic model of a two-link flexible manipulator based upon finite element and Lagrange's method is constructed. The dynamic model includes the effects of joint compliances and actuator dynamics. Friction is also incorporated in the dynamic model to account for stick-slip at the joints. Next, the friction parameters are to be determined. The identification problem is posed as an optimization problem to be solved using nonlinear programming methods. A genetic algorithm is used to increase the convergence rate and the chances of finding the global optimum. The identified friction parameters are experimentally verified and it is expected that the identification technique is applicable to a system parameter identification problem associated with a wide class of nonlinear systems.

A Study of Process Parameters Optimization Using Genetic Algorithm for Nd:YAG Laser Welding of AA5182 Aluminum Alloy Sheet (AA5182 알루미늄 판재의 Nd:YAG 레이저 용접에서 유전 알고리즘을 이용한 공정변수 최적화에 대한 연구)

  • Park, Young-Whan;Rhee, Se-Hun;Park, Hyun-Sung
    • Proceedings of the KSME Conference
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    • 2007.05a
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    • pp.1322-1327
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    • 2007
  • Many automotive companies have tried to apply the aluminum alloy sheet to car body because reducing the car weight can improve the fuel efficiency of vehicle. In order to do that, sheet materials require of weldablity, formability, productivity and so on. Aluminum alloy was not easy to join these metals due to its material properties. Thus, the laser is good heat source for aluminum alloy welding because of its high heat intensity. However, the welding quality was not good by porosity, underfill, and magnesium loss in welded metal for AA5182 aluminum alloy. In this study, Nd:YAG laser welding of AA 5182 with filler wire AA 5356 was carried out to overcome this problem. The weldability of AA5182 laser welding with AA5356 filler wire was investigated in terms of tensile strength and Erichsen ratio. For full penetration, mechanical properties were improved by filler wire. In order to optimize the process parameters, model to estimate tensile strength by artificial neural network was developed and fitness function was defined in consideration of weldability and productivity. Genetic algorithm was used to search the optimal point of laser power, welding speed, and wire feed rate.

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Optimization of operating parameters to remove and recover crude oil from contaminated soil using subcritical water extraction process

  • Taki, Golam;Islam, Mohammad Nazrul;Park, Seong-Jae;Park, Jeong-Hun
    • Environmental Engineering Research
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    • v.23 no.2
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    • pp.175-180
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    • 2018
  • Box-Behnken Design (BBD) under response surface methodology (RSM) was implemented to optimization the operating parameters and assess the removal and recovery efficiencies of crude oil from contaminated soil using subcritical water extraction. The effects of temperature, extraction time and water flow rate were explored, and the results indicate that temperature has a great impact on crude oil removal and recovery. The correlation coefficients for oil removal ($R^2=0.74$) and recovery ($R^2=0.98$) suggest that the proposed quadratic model is useful. When setting the target removal and recovery (>99%), BBD-RSM determined the optimum condition to be a temperature of $250^{\circ}C$, extraction time of 120 min, and water flow rate of 1 mL/min. An experiment was carried out to confirm the results, with removal and recovery efficiencies of 99.69% and 87.33%, respectively. This result indicates that BBD is a suitable method to optimize the process variables for crude oil removal and recovery from contaminated soil.

Human-like Balancing Motion Generation based on Double Inverted Pendulum Model (더블 역 진자 모델을 이용한 사람과 같은 균형 유지 동작 생성 기술)

  • Hwang, Jaepyung;Suh, Il Hong
    • The Journal of Korea Robotics Society
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    • v.12 no.2
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    • pp.239-247
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    • 2017
  • The purpose of this study is to develop a motion generation technique based on a double inverted pendulum model (DIPM) that learns and reproduces humanoid robot (or virtual human) motions while keeping its balance in a pattern similar to a human. DIPM consists of a cart and two inverted pendulums, connected in a serial. Although the structure resembles human upper- and lower-body, the balancing motion in DIPM is different from the motion that human does. To do this, we use the motion capture data to obtain the reference motion to keep the balance in the existence of external force. By an optimization technique minimizing the difference between the motion of DIPM and the reference motion, control parameters of the proposed method were learned in advance. The learned control parameters are re-used for the control signal of DIPM as input of linear quadratic regulator that generates a similar motion pattern as the reference. In order to verify this, we use virtual human experiments were conducted to generate the motion that naturally balanced.

Development of Optimal Design User Interface for Waveguide tee Junction using PSO Algorithm and VBA (PSO 알고리즘과 VBA를 이용한 Waveguide tee Junction의 최적설계 인터페이스 개발)

  • Park, Hyun-Soo;Byun, Jin-Kyu;Lee, Dal-Ho;Lee, Hyang-Beom
    • 한국정보통신설비학회:학술대회논문집
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    • 2009.08a
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    • pp.36-39
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    • 2009
  • We developed an optimal design interface based on VBA(Visual Basic Application) that takes advantage of API(Application Program Interface) function of commonly used EM analysis software. The developed interface is adopted for an optimal design of a septum in a waveguide tee junction using PSO(Particle Swarm Optimization) algorithm. The objective function of the optimal design is defined by $S_{11}$-parameter of the waveguide tee junction Design variables are established as position of the septum, that are changed to satisfy the design goal Using the developed design interface and PSO algorithm, the objective function converged to the smallest value, showing the validity of the proposed method. The design interface was developed using Microsoft Excel software, enabling easy control of design parameters for user. Also, various analysis parameters can be set in the Excel interface, including waveguide input mode and frequency. After completion of the design, field solutions at user-specified positrons can be extracted to the output files in complex number form.

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