• Title/Summary/Keyword: generalized inverse matrix

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Generalized Kinematics Modeling of Wheeled Mobile Robots (바퀴형 이동로봇의 기구학)

  • Shin, Dong-Hun;Park, Kyung-Hoon
    • Journal of the Korean Society for Precision Engineering
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    • v.19 no.5
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    • pp.118-125
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    • 2002
  • The previous kinematic analysis of wheeled mobile robots(WMRs) is performed in an ad-hoc manner, while those of the robot manipulators are done in a consistent way using the coordinate system assignment and the homogeneous transformation matrix. This paper shows why the method for the robot manipulators cannot be used directly to the WMRs and proposes the method for the WMRs, which contains modeling the wheel with the Sheth-Uicker notation and the homogeneous transformation. The proposed method enable us to model the velocity kinematics of the WMRs in a consistent way. As an implementation of the proposed method, the Jacobian matrices were obtained for conventional steered wheel and non-steered wheel respectively and the forward and inverse velocity kinematic solutions were calculated fur a tricycle typed WMR. We hope that our proposed method comes to hold an equivalent roles for WMRs, as that of the manipulators does for the robot manipulators.

Truss Ooptimization Using Homology Constraints under Multiple Loadings (호몰로지 제한조건을 이용한 다중하중하의 트러스 최적설계)

  • ;;;Kim, Kyung-Keun;Park, Gyung-Jin
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.20 no.9
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    • pp.2800-2811
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    • 1996
  • The deformation of a structure shall be called homologous, if a given geometrical relation holds, for a given number of structural points, before, during, and after the deformation. Some researchers have utilized the idea on structural design with finite element method. The approaches use the decomposition of the FEM equation or equality of eqality equations to obtain homologous deformation. However, weight reduction and response constraints such as stress, displacement or natural frequency cannot be considered by those theories. An optimization method solving the above problems is suggested to gain homologous deformation. Homology constraints can be considered under multiple loadindg conditions as well as a single loading condition. Homology index is defined for the multiple loading conditions Examples are solved to present the performances of the method.

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A study on kinematics and dynamics of robot arms by simulation (로봇 팔의 운동해석에 관한 연구)

  • 조선휘;김영일;임태홍
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.10 no.5
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    • pp.611-617
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    • 1986
  • In this paper, it is attempted to derive the minimum torque as the optimal value on each joint, which is applied during a PTP-motion in the range of working area of a supposed industrial robot. The rupposed industrial robot consits of 3-R joints prepared on three links, The optimizational analysis is performed by the formulation of a variational calculus process due to Rayleigh-Ritz method. That is, the torques of the inverse dynamic problem on joints in a arbitrary positions are computed by a generalized inertia matrix method.

Analysis of Stabilizing Process for the Unstable Truss Structures using a Topology of Member Connection (구성부재의 위상을 이용한 불안정 트러스 구조물의 안정화 이행과정)

  • 권택진;김진우;김재열
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2001.04a
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    • pp.251-258
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    • 2001
  • Cable and membrane structures can be classified as a unstable structure in the view point of shape determination process. An unstable stucture at the initial state generally cannot take a role as the resistance for the external force. Therefore, there should be a stabilizing process to get the stable state of a structure and it is necessary to visualize the shape finding from unstable state to stable state. In this paper, a numerical method of stabilizing procedure for the link structures is presented. The structures are assumed to have rigid movements and thus only changing of the topology of member is considered during the analysis. The generalized inverse matrix and the principle of minimum potential energy are used in the process. Illustrative examples are presented and the results show good convergence.

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Variable Selection Theorem for the Analysis of Covariance Model (공분산분석 모형에서의 변수선택 정리)

  • Yoon, Sang-Hoo;Park, Jeong-Soo
    • Communications for Statistical Applications and Methods
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    • v.15 no.3
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    • pp.333-342
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    • 2008
  • Variable selection theorem in the linear regression model is extended to the analysis of covariance model. When some of regression variables are omitted from the model, it reduces the variance of the estimators but introduces bias. Thus an appropriate balance between a biased model and one with large variances is recommended.

Structural Homology Design Using Equality Constraints (등제한조건 함수를 이용한 구조물의 호몰로지 설계)

  • Lee, Gwon-Hui;Park, Gyeong-Jin
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.20 no.3
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    • pp.872-881
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    • 1996
  • The concept of homology design has been devised for the application to large telescope structure by S.v.Hoerner. It is defined that the deformation of a structure shall be called homologous, if a given geometrical relation holds, for a given number of structural points, before, during, and after the deformation. Recently, the need of homology design in the structural design has been increase due to the required precision in the structure. Some researchers have utilized the theory on the structural design with finite element method in the late 1980s In the present investigation, a simple method using geometrical equality constraints is suggested to gain homologous deformation. The previous method is improved in that the decomposition of FEM eqation, which is very expensive, is not necessary. The basic formulations of the homology design with the optimization concept are described and several practical examples are solved to verify the usefulness and validity. Especially, a back-up structure of a satellite antenna is designed by the suggested method. The results are compared with those of existing researches.

The Structure and the Convergence Characteristics Analysis on the Generalized Subband Decomposition FIR Adaptive Filter in Wavelet Transform Domain (웨이블릿 변환을 이용한 일반화된 서브밴드 분해 FIR 적응 필터의 구조와 수렴특성 해석)

  • Park, Sun-Kyu;Park, Nam-Chun
    • Journal of the Institute of Convergence Signal Processing
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    • v.9 no.4
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    • pp.295-303
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    • 2008
  • In general, transform domain adaptive filters show faster convergence speed than the time domain adaptive filters, but the amount of calculation increases dramatically as the filter order increases. This problem can be solved by making use of the subband structure in transform domain adaptive filters. In this paper, to increase the convergence speed on the generalized subband decomposition FIR adaptive filters, a structure of the adaptive filter with subfilter of dyadic sparsity factor in wavelet transform domain is designed. And, in this adaptive filter, the equivalent input in transform domain is derived and, by using the input, the convergence properties for the LMS algorithm is analyzed and evaluated. By using this sub band adaptive filter, the inverse system modeling and the periodic noise canceller were designed, and, by computer simulation, the convergence speeds of the systems on LMS algorithm were compared with that of the subband adaptive filter using DFT(discrete Fourier transform).

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Simple factor analysis of measured data

  • Kozar, Ivica;Kozar, Danila Lozzi;Malic, Neira Toric
    • Coupled systems mechanics
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    • v.11 no.1
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    • pp.33-41
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    • 2022
  • Quite often we have a lot of measurement data and would like to find some relation between them. One common task is to see whether some measured data or a curve of known shape fit into the cumulative measured data. The problem can be visualized since data could generally be presented as curves or planes in Cartesian coordinates where each curve could be represented as a vector. In most cases we have measured the cumulative 'curve', we know shapes of other 'curves' and would like to determine unknown coefficients that multiply the known shapes in order to match the measured cumulative 'curve'. This problem could be presented in more complex variants, e.g., a constant could be added, some missing (unknown) data vector could be added to the measured summary vector, and instead of constant factors we could have polynomials, etc. All of them could be solved with slightly extended version of the procedure presented in the sequel. Solution procedure could be devised by reformulating the problem as a measurement problem and applying the generalized inverse of the measurement matrix. Measurement problem often has some errors involved in the measurement data but the least squares method that is comprised in the formulation quite successfully addresses the problem. Numerical examples illustrate the solution procedure.

COMPARISONS OF PARALLEL PRECONDITIONERS FOR THE COMPUTATION OF SMALLEST GENERALIZED EIGENVALUE

  • Ma, Sang-Back;Jang, Ho-Jong;Cho, Jae-Young
    • Journal of applied mathematics & informatics
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    • v.11 no.1_2
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    • pp.305-316
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    • 2003
  • Recently, an iterative algorithm for finding the interior eigenvalues of a definite matrix by CG-type method has been proposed. This method compares to the inverse power method. The given matrices A, and B are assumed to be large and sparse, and SPD( Symmetric Positive Definite) The CG scheme for the optimization of the Rayleigh quotient has been proven a very attractive and promising technique for large sparse eigenproblems for smallest eigenvalue. Also, it is very amenable to parallel computations, like the CG method for the linear systems. A proper choice of the preconditioner significantly improves the convergence of the CG scheme. But for parallel computations we need to find an efficient parallel preconditioner. Our candidates we ILU(0) in the wave-front order, ILU(0) in the multi-coloring order, Point-SSOR(Symmetric Successive Overrelaxation), and Multi-Color Block SSOR preconditioner. Wavefront order is a simple way to increase parallelism in the natural order, and Multi-coloring realizes a parallelism of order(N), where N is the order of the matrix. Another choice is the Multi-Color Block SSOR(Symmetric Successive OverRelaxation) preconditioning. Block SSOR is a symmetric preconditioner which is expected to minimize the interprocessor communication due to the blocking. We implemented the results on the CRAY-T3E with 128 nodes. The MPI (Message Passing Interface) library was adopted for the interprocessor communications. The test problem was drawn from the discretizations of partial differential equations by finite difference methods. The results show that for small number of processors Multi-Color ILU(0) has the best performance, while for large number of processors Multi-Color Block SSOR performs the best.

Solution of randomly excited stochastic differential equations with stochastic operator using spectral stochastic finite element method (SSFEM)

  • Hussein, A.;El-Tawil, M.;El-Tahan, W.;Mahmoud, A.A.
    • Structural Engineering and Mechanics
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    • v.28 no.2
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    • pp.129-152
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    • 2008
  • This paper considers the solution of the stochastic differential equations (SDEs) with random operator and/or random excitation using the spectral SFEM. The random system parameters (involved in the operator) and the random excitations are modeled as second order stochastic processes defined only by their means and covariance functions. All random fields dealt with in this paper are continuous and do not have known explicit forms dependent on the spatial dimension. This fact makes the usage of the finite element (FE) analysis be difficult. Relying on the spectral properties of the covariance function, the Karhunen-Loeve expansion is used to represent these processes to overcome this difficulty. Then, a spectral approximation for the stochastic response (solution) of the SDE is obtained based on the implementation of the concept of generalized inverse defined by the Neumann expansion. This leads to an explicit expression for the solution process as a multivariate polynomial functional of a set of uncorrelated random variables that enables us to compute the statistical moments of the solution vector. To check the validity of this method, two applications are introduced which are, randomly loaded simply supported reinforced concrete beam and reinforced concrete cantilever beam with random bending rigidity. Finally, a more general application, randomly loaded simply supported reinforced concrete beam with random bending rigidity, is presented to illustrate the method.