• Title/Summary/Keyword: least square minimization

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A Commutation Torque Minimization Method for Brushless DC Motors with Trapezoidal Elecromotive Force

  • Kim, Chang-Gyun;Lee, Joong-Hui;Youn, Myung-Joong
    • Proceedings of the KIPE Conference
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    • 1998.10a
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    • pp.476-481
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    • 1998
  • In this paper, a commutation torque minimization method using parameter observer for a brushless DC motor fed by a voltage source inverter is described. In order to investigate the nature of the commutation torque ripple in trapezoidal brushless DC motor, a new model of the motor is proposed. The optimal drive voltage to minimize the ripple torque is represented as a function of the motor parameters. Therefore, the important parameter is estimated by least-square algorithm.

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Harmonic Response Estimation Method on the Lévy Plate with Two Opposite Edges Having Free Boundary Conditions (마주보는 양단이 자유 경계조건을 갖는 Lévy 판의 조화 응답 해석)

  • Park, Nam-Gyu;Suh, Jung-Min;Jeon, Kyeong-Lak
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.23 no.11
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    • pp.943-950
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    • 2013
  • This paper discusses a harmonic response estimation method on the L$\acute{e}$vy plate with two opposite edges simply supported and the other two edges having free boundary conditions. Since the equation of motion of the plate is not self-adjoint, the modes are not orthogonal to each other on the domain. Noting that the L$\acute{e}$vy plate can be expressed using one term sinusoidal function that is orthogonal to other sinusoidal functions, this paper suggested the calculation method that is equivalent to finding a least square error minimization solution of the finite number of algebraic equations. Example problems subjected to a distributed area loading and a distributed line loading are defined and their solutions are provided. The solutions are compared to those of the commercial code, ANSYS. According to the verification results, it is expected that the suggested method will be useful to predict the forced response on the L$\acute{e}$vy plate with the distributed area or line loading conditions.

Reference Frame Approach for Torque Ripple Minimization of BLDCM over Wide Speed Range Including Cogging Torque (코깅 토크를 포함한 광역 속도 영역상의 BLDCM의 토크 리플 최소화를 위한 기준 프레임 접근기법)

  • Park, Han-Woong;Cho, Sung-Bae;Won, Tae-Hyun;Kwon, Soon-Jae;Ham, Byung-Woon;Kim, Cheul-U
    • Proceedings of the KIEE Conference
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    • 2001.04a
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    • pp.33-36
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    • 2001
  • Torque ripple control of brush less DC motor has been the main issue of the servo drive systems in which the speed fluctuation, vibration and acoustic noise should be minimized. Most methods for suppressing the torque ripples require Fourier series analysis and either the iterative or least mean square minimization. In this paper, the novel approach to achieve the ripple-tree torque control with maximum efficiency based on the d-q-0 reference frame is presented. The proposed method optimize the reference phase current waveforms including even the case of 3 phase unbalanced condition, and the motor winding currents are controlled to follow up the optimized current waveforms by delta modulation technique. As a result, the proposed approach provides a simple and clear way to obtain the optimal motor excitation currents. The validity and practical applications of the proposed control scheme are verified through the simulations and experimental results.

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Multiobjective Space Search Optimization and Information Granulation in the Design of Fuzzy Radial Basis Function Neural Networks

  • Huang, Wei;Oh, Sung-Kwun;Zhang, Honghao
    • Journal of Electrical Engineering and Technology
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    • v.7 no.4
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    • pp.636-645
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    • 2012
  • This study introduces an information granular-based fuzzy radial basis function neural networks (FRBFNN) based on multiobjective optimization and weighted least square (WLS). An improved multiobjective space search algorithm (IMSSA) is proposed to optimize the FRBFNN. In the design of FRBFNN, the premise part of the rules is constructed with the aid of Fuzzy C-Means (FCM) clustering while the consequent part of the fuzzy rules is developed by using four types of polynomials, namely constant, linear, quadratic, and modified quadratic. Information granulation realized with C-Means clustering helps determine the initial values of the apex parameters of the membership function of the fuzzy neural network. To enhance the flexibility of neural network, we use the WLS learning to estimate the coefficients of the polynomials. In comparison with ordinary least square commonly used in the design of fuzzy radial basis function neural networks, WLS could come with a different type of the local model in each rule when dealing with the FRBFNN. Since the performance of the FRBFNN model is directly affected by some parameters such as e.g., the fuzzification coefficient used in the FCM, the number of rules and the orders of the polynomials present in the consequent parts of the rules, we carry out both structural as well as parametric optimization of the network. The proposed IMSSA that aims at the simultaneous minimization of complexity and the maximization of accuracy is exploited here to optimize the parameters of the model. Experimental results illustrate that the proposed neural network leads to better performance in comparison with some existing neurofuzzy models encountered in the literature.

Pseudoinverse Matrix Decomposition Based Incremental Extreme Learning Machine with Growth of Hidden Nodes

  • Kassani, Peyman Hosseinzadeh;Kim, Euntai
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.2
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    • pp.125-130
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    • 2016
  • The proposal of this study is a fast version of the conventional extreme learning machine (ELM), called pseudoinverse matrix decomposition based incremental ELM (PDI-ELM). One of the main problems in ELM is to determine the number of hidden nodes. In this study, the number of hidden nodes is automatically determined. The proposed model is an incremental version of ELM which adds neurons with the goal of minimization the error of the ELM network. To speed up the model the information of pseudoinverse from previous step is taken into account in the current iteration. To show the ability of the PDI-ELM, it is applied to few benchmark classification datasets in the University of California Irvine (UCI) repository. Compared to ELM learner and two other versions of incremental ELM, the proposed PDI-ELM is faster.

Detection of Second-Layer Corrosion in Aging Aircraft Fuselage

  • Kim, Noh-Yu;Achenbach, J.D.
    • Journal of the Korean Society for Nondestructive Testing
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    • v.26 no.6
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    • pp.417-426
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    • 2006
  • A Digital X-ray imaging system using Compton backscattering has been developed to obtain a cross-sectional profile and mass loss of corroded lap-splices of aging aircraft from density variation. A slit-type camera was designed to focus on a small scattering volume inside the material, from which the backscattered photons are collected by a collimated scintillator detector for interpretation of material characteristics. The cross section of the lap-joint is scanned by moving the scattering volume through the thickness direction of the specimen. The mass loss of each layer has been estimated from a Compton backscatter A-scan to obtain the thickness of each layer including the aluminum sheet, the corrosion layer and the sealant. Quantitative information such as location and width of planar corrosion in the lap splices of fuselages is obtained by deconvolution using a nonlinear least-square error minimization method(BFGS method): A simple reconstruction model is also introduced to overcome distortion of the Compton backscatter data due to attenuation effects attributed to beam hardening and quantum noise.

Self-Tuning Position Control of a Remotely Operated Vehicle (원격무인 잠수정의 자기동조 위치제어)

  • Lee, Pan-Muk
    • Journal of Ocean Engineering and Technology
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    • v.3 no.2
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    • pp.551-551
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    • 1989
  • In general, a remotely operated vehicle(ROV) operates at deep sea. The control system of ROV is composed of two local loops; the first loop placed on the surface vessel monitors and manipulates the attitude of the ROV using joystick, and the second part on the ROV automatically controls thrusters and acquires positional data. This paper presents a position control simulation of a ROV using an adaptive controller and discusses the control effects of two different conditions. The design of an adaptive control system is obtained by the application of a self-tuning controller with the minimization of an appropriate cost function. The parameters of the control system are estimated by a recursive least square method(RLS). In the simulation, a Runge-Kutta method is used for the numerical integration and the generated outputs are obtained by adding measurement errors. Additionally, this paper discusses the mathematical modelling of a ROV and make a survey of control systems.

Self-Tuning Position Control of a Remotely Operated Vehicle (원격무인 잠수정의 자기동조 위치제어)

  • Lee, Pan-Muk
    • Journal of Ocean Engineering and Technology
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    • v.3 no.2
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    • pp.51-58
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    • 1989
  • In general, a remotely operated vehicle(ROV) operates at deep sea. The control system of ROV is composed of two local loops; the first loop placed on the surface vessel monitors and manipulates the attitude of the ROV using joystick, and the second part on the ROV automatically controls thrusters and acquires positional data. This paper presents a position control simulation of a ROV using an adaptive controller and discusses the control effects of two different conditions. The design of an adaptive control system is obtained by the application of a self-tuning controller with the minimization of an appropriate cost function. The parameters of the control system are estimated by a recursive least square method(RLS). In the simulation, a Runge-Kutta method is used for the numerical integration and the generated outputs are obtained by adding measurement errors. Additionally, this paper discusses the mathematical modelling of a ROV and make a survey of control systems.

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A Study on digital Controller for Power System Stabilization (전력 계통 안정화 제어를 위한 이산시간 제어기 설계)

  • Park, Young-Moon;Hyun, Seung-Ho
    • Proceedings of the KIEE Conference
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    • 1992.07a
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    • pp.135-137
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    • 1992
  • A new algorithm for self-tuning digital controller is proposed. The system to be controlled is identified on line in auto-regressive-moving-average(ARMA) form via recursive least mean square method. The control law is obtained from the minimization of an objective function. The proposed objective function is similar to that of Generalized Minimum Variance(GMV) method but modified to lessen the overshoot and to avoid numerical divergence problem. This algorithm is applied to the power system stabilization and the comparison of the proposed method with a conventional power system stabilizer(PSS) is presented.

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A Shape Finding and Cutting Pattern Determination for Membrane Structures (막 구조물에 관한 형상 탐색과 재단도 결정법)

  • Choi, Ho;Lee, Jang-Bog;Kim, Jae-Yeol;Sur, Sam-Uel;Kwon, Taek-Jin
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1998.04a
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    • pp.175-182
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    • 1998
  • The object of this study is shape finding and cutting pattern generation of membrane structures under the following assumptions : (1) material is linearly elastic (2) stress state is plane stress. Cable and membrane structures should introduce the nonlinear analysis considering geometric nonlinearity because these structures deform largely under the external loads. The analysis procedure is consisted of three steps considering geometric nonlinearity unlike any other structures. First step is the shape finding analysis to determine the initial equilibrium shape. Second step is the stress-deformation analysis to investigate the behaviors of structures under various external loads. Once a satisfactory shape has been found, a cutting pattern based on the shape finding analysis may be generated from the view point of construction. In this paper, (1) shape finding analysis formulation and an example, (2) cutting pattern determination procedure using weighted least-square minimization flattening method and some results are presented.

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