• Title/Summary/Keyword: adjustable parameter

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Sensorless Control Method of Single-Phase hybrid SRM (단상 하이브리드 SRM의 센서리스 제어기법)

  • Tang, Ying;Zhang, Fengge;Lee, Dong-Hee;Ahn, Jin-Woo
    • Proceedings of the KIPE Conference
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    • 2015.11a
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    • pp.213-214
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    • 2015
  • In this paper, a novel method of sensorless control scheme is proposed to apply on a single phase hybrid SRM used in high speed operation. The proposed method utilizes beneficially permanent magnet field whose performance is motor parameter independent to estimate the rotor position. The differential value of back-EMF is used to detect its peak point when there is no current conducting in the winding. Through this approach, the adjustable turn on/off position can be achieved without prior knowledge of inductance profile which is always employed by many sensorless schemes. And this paper may offer an available method to do the sensorless control in hybrid SRM used for high speed running.

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A Proposal of a Correlation of the Enthalpy of Vaporization for Pure Substances and Performance Comparison of Correlations (순수물질에 대한 증발엔탈피 상관식의 제안 및 성능비교)

  • Lee, Kyoung-Youl;Park, Kyoung-Kuhn
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.17 no.12
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    • pp.1185-1191
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    • 2005
  • Published correlation equations of the enthalpy of vaporization are reviewed and a new four-parameter correlation equation is proposed. Performance of the proposed equation is examined using the ASHRAE data for 22 pure substance refrigerants as reference data. The new equation yields an average absolute deviation of $0.05\%$, which is smaller than those of published equations, such as equations of Guermouche-Vergnaund $(0.08\%)$, Aerebrot $(0.13\%)$, Radoz-Lydersen $(0.08\%)$, and Somayajulu $(0.08\%)$. The three adjustable parameters of the modified correlation are optimized and reported for 22 substances. The equation proposed in this work is valid over the entire temperature range where data points exist.

Design formulas for vibration control of sagged cables using passive MR dampers

  • Duan, Yuanfeng;Ni, Yi-Qing;Zhang, Hongmei;Spencer, Billie F. Jr.;Ko, Jan-Ming;Dong, Shenghao
    • Smart Structures and Systems
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    • v.23 no.6
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    • pp.537-551
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    • 2019
  • In this paper, a method for analyzing the damping performance of stay cables incorporating magnetorheological (MR) dampers in the passive control mode is developed taking into account the cable sag and inclination, the damper coefficient, stiffness and mass, and the stiffness of damper support. Both numerical and asymptotic solutions are obtained from complex modal analysis. With the asymptotic solution, analytical formulas that evaluate the equivalent damping ratio of the sagged cable-damper system in consideration of all the above parameters are derived. The main thrust of the present study is to develop an general design formula and a universal curve for the optimal design of MR dampers for adjustable passive control of sagged cables. Two sag-affecting coefficients are derived to reflect the effects of cable sag on the maximum attainable damping ratio and the optimal damper coefficient. For the cable configurations commonly used in cable-stayed bridges, the sag-affecting coefficients are directly expressed in terms of the sag-extensibility parameter to facilitate the control design. A case study on adjustable passive vibration control of the longest cable (536 m) on Stonecutters Bridge is carried out to demonstrate the influence of the sag for the damper design, and to figure out the necessity of adjustability of damper coefficients for achieving maximum damping ratio for different vibration modes.

Neural Network Structure and Parameter Optimization via Genetic Algorithms (유전알고리즘을 이용한 신경망 구조 및 파라미터 최적화)

  • 한승수
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.3
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    • pp.215-222
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    • 2001
  • Neural network based models of semiconductor manufacturing processes have been shown to offer advantages in both accuracy and generalization over traditional methods. However, model development is often complicated by the fact that back-propagation neural networks contain several adjustable parameters whose optimal values unknown during training. These include learning rate, momentum, training tolerance, and the number of hidden layer neurOnS. This paper presents an investigation of the use of genetic algorithms (GAs) to determine the optimal neural network parameters for the modeling of plasma-enhanced chemical vapor deposition (PECVD) of silicon dioxide films. To find an optimal parameter set for the neural network PECVD models, a performance index was defined and used in the GA objective function. This index was designed to account for network prediction error as well as training error, with a higher emphasis on reducing prediction error. The results of the genetic search were compared with the results of a similar search using the simplex algorithm.

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Parameter Optimization of the Marine Gyrocompass Follow-up System (자이로콤파스 추종계통의 최적조정)

  • 이상집
    • Journal of the Korean Institute of Navigation
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    • v.5 no.2
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    • pp.49-58
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    • 1981
  • One of the main purposes of the marine gyrocompass follow-up system is to preserve the sensitive part from the wandering error due to the frictional or torsional torque around the vertical axis. This error can be diminished through the rapid follow-up action, which minimizes the relative azimuthal angular displacement between the sensitive and follow-up parts and shortens the duration of the same displacement. But an excessive rapidity of the follow-up action would result in a sustained oscillation to the system. Therefore, to design a new type of the follow-up system, the theoretical annlysis of the problems concerned should be studied systematically by introducing the control theory. This paper suggest a concrete procedure for the optimal adjustment of the gyrocompass follow-up system, utilizing the mathematic model and the stability informations formerly investiaged by the author. For theoptimal determination of the adjustable paramfter K, the performance index(P.I.), ITSE(Intergral of the Time multiplied by the Squared Error) is proposed, namely, P.I. = $\int_{0}^{\infty} t \cdot e^{2}(t)dt$ where t is time and e(t) means control error. Then, the optimal parameter minimizing the performance index is calculated by means of Parseval's theorem and numerical computation, and the validity of the obtained optimal value of the parameter Ka is examined and confirmed through the simulations and experiments. By using, the proposed method, the optimal adjustment can be performed deterministically. But, this can not be expected in the conventional frequency domain analysis. While the Mps of the original system vary to the extent of from 0.98 to 46.27, Mp of the optimal system is evaluated as 1.1 which satisfies the generally accepted frequency domain specification.

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A Study on the Control Parameter Tuning Method of the Hyundai 8608 Robot (Hyundai 8608 Robot 제어기 파라미터 튜닝 방안 연구)

  • Kim Mi-Kyung;Yoon Cheon-Seok;Kang Hee-Jun;Suh Young-Soo;Ro Young-Shick;Son Hong-Rae
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.06a
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    • pp.1836-1840
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    • 2005
  • This work proposes a controller tuning method of a Hyundai 8608 robot in order to improve its performance. For this, we analyzed the control structure of the robot, and the functions of all the adjustable parameters in the robot controller with a reference 'NACHI Technical Report'. Through the analysis, we found out that 3 important parameters(VRRL, VRF, VRGIN) act like a conventional PID gains and other parameters are closely related to these 3 parameters. Conclusively, parameter tuning of these 3 parameters is enough in most cases of applications with other parameters fixed. The conventional PID tuning is performed to each joint of the test robot with Robot Performance Evaluation System(shown in our companion paper) so that the acceptable gain ranges for each joint are determined and then the robot performance tests are repeatedly done with the combination of the acceptable gains. Finally, the best combination is selected for its best performance. For the effectiveness of the proposed method, it was implemented on a Hyundai 8608 robot and its results are compared with the results of NACHI's Semi-Auto Tuning Method and the results which are done by a tuning expert with his eyes.

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Stochastic vibration suppression analysis of an optimal bounded controlled sandwich beam with MR visco-elastomer core

  • Ying, Z.G.;Ni, Y.Q.;Duan, Y.F.
    • Smart Structures and Systems
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    • v.19 no.1
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    • pp.21-31
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    • 2017
  • To control the stochastic vibration of a vibration-sensitive instrument supported on a beam, the beam is designed as a sandwich structure with magneto-rheological visco-elastomer (MRVE) core. The MRVE has dynamic properties such as stiffness and damping adjustable by applied magnetic fields. To achieve better vibration control effectiveness, the optimal bounded parametric control for the MRVE sandwich beam with supported mass under stochastic and deterministic support motion excitations is proposed, and the stochastic and shock vibration suppression capability of the optimally controlled beam with multi-mode coupling is studied. The dynamic behavior of MRVE core is described by the visco-elastic Kelvin-Voigt model with a controllable parameter dependent on applied magnetic fields, and the parameter is considered as an active bounded control. The partial differential equations for horizontal and vertical coupling motions of the sandwich beam are obtained and converted into the multi-mode coupling vibration equations with the bounded nonlinear parametric control according to the Galerkin method. The vibration equations and corresponding performance index construct the optimal bounded parametric control problem. Then the dynamical programming equation for the control problem is derived based on the dynamical programming principle. The optimal bounded parametric control law is obtained by solving the programming equation with the bounded control constraint. The controlled vibration responses of the MRVE sandwich beam under stochastic and shock excitations are obtained by substituting the optimal bounded control into the vibration equations and solving them. The further remarkable vibration suppression capability of the optimal bounded control compared with the passive control and the influence of the control parameters on the stochastic vibration suppression effectiveness are illustrated with numerical results. The proposed optimal bounded parametric control strategy is applicable to smart visco-elastic composite structures under deterministic and stochastic excitations for improving vibration control effectiveness.

Development of Electrical Stimulator for Auditory Stimulation (청각 자극용 전기자극기 개발)

  • Heo, Seung-Deok;Jung, Dong-Keun;Kim, Lee-Suk;Kim, Gwang-Nyeon;Kang, Myung-Koo;Kim, Jae-Ryong;Kim, Gi-Ryon
    • Speech Sciences
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    • v.11 no.3
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    • pp.201-211
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    • 2004
  • This paper introduces a development of an electrical stimulator for auditory stimulation. The electrical stimulator is useful in neurotological diagnosis, audiological evaluation, candidate selection for cochlear implantation, optimal device selection and decision making of MAP strategy for severe-to-profound hearing impaired persons. The development was based on sound parameters of auditory brainstem responses and auditory electrophysiological characteristic such as effective firing of auditory nerve and recording evoked potentials during refractory period of neuron. Besides pulse parameter could adjustable by programming for more varied electrical stimulation evoked response audiometry. Using the electrical stimulator, electrical square pulse was applied to promontory, and electrically evoked auditory brainstem response and electrically middle latency response were successfully recorded in cats.

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BJRNAFold: Prediction of RNA Secondary Structure Base on Constraint Parameters

  • Li, Wuju;Ying, Xiaomin
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2005.09a
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    • pp.287-293
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    • 2005
  • Predicting RNA secondary structure as accurately as possible is very important in functional analysis of RNA molecules. However, different prediction methods and related parameters including terminal GU pair of helices, minimum length of helices, and free energy systems often give different prediction results for the same RNA sequence. Then, which structure is more important than the others? i.e. which combinations of the methods and related parameters are the optimal? In order to investigate above problems, first, three prediction methods, namely, random stacking of helical regions (RS), helical regions distribution (HD), and Zuker's minimum free energy algorithm (ZMFE) were compared by taking 1139 tRNA sequences from Rfam database as the samples with different combinations of parameters. The optimal parameters are derived. Second, Zuker's dynamic programming method for prediction of RNA secondary structure was revised using the above optimal parameters and related software BJRNAFold was developed. Third, the effects of short-range interaction were studied. The results indicated that the prediction accuracy would be improved much if proper short-range factor were introduced. But the optimal short-range factor was difficult to determine. A user-adjustable parameter for short-range factor was introduced in BJRNAFold software.

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High Performance Speed Control of IPMSM Drive using Recurrent FNN Controller (순환 퍼지뉴로 제어기를 이용한 IPMSM 드라이브의 고성능 속도제어)

  • Ko, Jae-Sub;Chung, Dong-Hwa
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.9
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    • pp.1700-1707
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    • 2011
  • Interior permanent magnet synchronous motor(IPMSM) adjustable speed drives offer significant advantages over induction motor drives in a wide variety of industrial applications such as high power density, high efficiency, improved dynamic performance and reliability. Since the fuzzy neural network(FNN) is recognized general approximate method to control non-linearities and uncertainties, the development of FNN control systems have also grown rapidly. The FNN controller is compounded of fuzzy and neural network. It has an advantage that is the robustness of fuzzy control and the ability to adapt of neural network. However, the FNN has static problem due to their feed-forward network structure. This paper proposes high performance speed control of IPMSM drive using the recurrent FNN(RFNN) which improved conventional FNN controller. The RFNN has excellent dynamic response characteristics because of it has internally feed-back structure. Also, this paper proposes speed estimation of IPMSM drive using ANN. The proposed method is analyzed and compared to conventional FNN controller in various operating condition such as parameter variation, steady and transient states etc.