• Title/Summary/Keyword: approximation with constraints

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A Method for Modifying a Surface Model with Nonuniform Scattered Constraint Points (불균일 이산 구속조건을 만족시키는 곡면 모델의 변형 방법)

  • Kim, S.H.;Song, S.J.
    • Korean Journal of Computational Design and Engineering
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    • v.12 no.1
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    • pp.58-73
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    • 2007
  • This paper described a method for the construction of a surface through a set of nonuniform scattered points. When the shift vectors of some points as constraints on the original surface are given, those of the other points should be computed to make the new surface. To keep up the look-see and smoothness with the original surfaces, the proper relationship should be formulated between the shifts of the constraint points and those of the other points. Vector fields for 3 dimensional shift of a point on the surface are made based in the constraint shifts. Vector fields for 3 dimensional shift of a point on the surface are made based on the constraint shifts. Multilevel B-spline approximation technique was used to construct the vector field. The technique uses coarse-to-fine hierarchy of control lattices. The developed method was applied to shoe sole design system especially for grading. Using this system, a shoe sole can be modified effectively.

A Minimum time trajectory planning for robotic manipulators with input torque constraint (입력 토오크 constraint를 가진 로보트 매니플레이터에 대한 최소 시간 궤적 계획)

  • Hong, In-Keun;Hong, Suk-Kyo
    • Proceedings of the KIEE Conference
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    • 1989.11a
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    • pp.445-449
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    • 1989
  • Achievement of a straight line motion in the Cartesian space has a matter of great importance. Minimization of task execution time with linear interpolation in the joint space, accomplishing of a approximation of straight line motion in the Cartesian coordinate is considered as the prespecified task. Such determination yields minimum time joint-trajectory subject to input torque constraints. The applications of these results for joint-trajectory planning of a two-link manipulator with revolute joints are demonstrated by computer simulations.

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Shape Optimization of Three-Dimensional Continuum Structures by Force Approximation Techniques (힘 근사화 기법에 의한 3차원 연속체 구조물의 형상최적화)

  • Han, Sang Hoon;Lee, Woong Jong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.13 no.1
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    • pp.39-46
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    • 1993
  • The need to develop method which can improve the shape design efficiency using high quality approximation is being brought up. In this study, to perform shape optimal design of three-dimensional continuum structures an efficient approximation method for stress constraints is proposed, based on expanding the nodal forces in Taylor series with respect to shape variables. Numerical examples are performed using the 3-D cantilever beam and fixed-fixed beam and compared with other method to demonstrate the efficiency and convergence rate of the Force Approximation method. It is shown that by taking advantage of this high quality approximation, the total number of finite element analysis required for shape optimization of 3-D continuum structures can be reduced significantly, resulting to the same level of efficiency achieved previously in sizing optimization problems. Also, shape representation by super curve technique applied to obtain optimal shape finds useful method.

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Dynamic Survivable Routing for Shared Segment Protection

  • Tapolcai, Janos;Ho, Pin-Han
    • Journal of Communications and Networks
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    • v.9 no.2
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    • pp.198-209
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    • 2007
  • This paper provides a thorough study on shared segment protection (SSP) for mesh communication networks in the complete routing information scenario, where the integer linear program (ILP) in [1] is extended such that the following two constraints are well addressed: (a) The restoration time constraint for each connection request, and (b) the switching/merging capacity constraint at each node. A novel approach, called SSP algorithm, is developed to reduce the extremely high computation complexity in solving the ILP formulation. Basically, our approach is to derive a good approximation on the parameters in the ILP by referring to the result of solving the corresponding shared path protection (SPP) problem. Thus, the design space can be significantly reduced by eliminating some edges in the graphs. We will show in the simulation that with our approach, the optimality can be achieved in most of the cases. To verify the proposed formulation and investigate the performance impairment in terms of average cost and success rate by the additional two constraints, extensive simulation work has been conducted on three network topologies, in which SPP and shared link protection (SLP) are implemented for comparison. We will demonstrate that the proposed SSP algorithm can effectively and efficiently solve the survivable routing problem with constraints on restoration time and switching/merging capability of each node. The comparison among the three protection types further verifies that SSP can yield significant advantages over SPP and SLP without taking much computation time.

Optimal Design of Frame Structure Considering Buckling Load (좌굴하중을 고려한 프레임 그조물의 최적 설계)

  • 진경욱
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.9 no.2
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    • pp.59-65
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    • 2000
  • In this paper the comparison of the first order approximation schemes such as SLP(sequential linear programming) CONLIN(convex linearization) MMA(method of moving asymptotes) and the second order approximation scheme SQP(sequential quadratic programming) was accomplished for optimization of nonlinear structures. It was found that MMA and SQP are the most efficient methods for optimization. But the number of function call of SQP is much more than that of MMA. Therefore when it is considered with the expense of computation MMA is more efficient than SQP. In order to examine the efficiency of MMA for complex optimization problem it was applied to the helicopter tail boom con-sidering column buckling and local wall buckling constraints. it is concluded that MMA can be a very efficient approxima-tion scheme from simple problems to complex problems.

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Adaptive Neural Control for Output-Constrained Pure-Feedback Systems (출력 제약된 Pure-Feedback 시스템의 적응 신경망 제어)

  • Kim, Bong Su;Yoo, Sung Jin
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.1
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    • pp.42-47
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    • 2014
  • This paper investigates an adaptive approximation design problem for the tracking control of output-constrained non-affine pure-feedback systems. To satisfy the desired performance without constraint violation, we employ a barrier Lyapunov function which grows to infinity whenever its argument approaches some limits. The main difficulty in dealing with pure-feedback systems considering output constraints is that the system has a non-affine appearance of the constrained variable to be used as a virtual control. To overcome this difficulty, the implicit function theorem and mean value theorem are exploited to assert the existence of the desired virtual and actual controls. The function approximation technique based on adaptive neural networks is used to estimate the desired control inputs. It is shown that all signals in the closed-loop system are uniformly ultimately bounded.

Application of Method of Moving Asymptotes for Non-Linear Structures (비선형 구조물에 대한 이동 점근법(MMA)의 적용)

  • 진경욱;한석영;최동훈
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 1999.05a
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    • pp.141-146
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    • 1999
  • A new method, so called MMA(Method of Moving Asymptotes) was applied to the optimization problems of non-linear functions and non-linear structures. In each step of the iterative process, tile MMA generates a strictly convex approximation subproblems and solves them by using the dual problems. The generation of these subproblems is controlled by so called 'moving asymptotes', which may both make no oscillation and speed up tile convergence rate of optimization process. By contrast in generalized dual function, the generated function by MMA is always explicit type. Both the objective and behaviour constraints which were approximated are optimized by dual function. As the results of some examples, it was found that this method is very effective to obtain the global solution for problems with many local solutions. Also it was found that MMA is a very effective approximate method using the original function and its 1st derivatives.

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Multilayer Stereo Image Matching Based upon Phase-Magnitude an Mean Field Approximation

  • Hong Jeong;Kim, Jung-Gu;Chae, Myoung-Sik
    • Journal of Electrical Engineering and information Science
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    • v.2 no.5
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    • pp.79-88
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    • 1997
  • This paper introduces a new energy function, as maximum a posteriori(MAP) estimate of binocular disparity, that can deal with both random dot stereo-gram(RDS) and natural scenes. The energy function uses phase-magnitude as features to detect only the shift for a pair of corrupted conjugate images. Also we adopted Fleet singularity that effectively detects unstable areas of image plant and thus eliminates in advance error-prone stereo mathcing. The multi-scale concept is applied to the multi laser architecture that can search the solutions systematically from coarse to fine details and thereby avoids drastically the local minima. Using mean field approximation, we obtained a compact representation that is suitable for fast computation. In this manner, the energy function satisfies major natural constraints and requirements for implementing parallel relaxation. As an experiment, the proposed algorithm is applied to RDS and natural stereo images. As a result we will see that it reveals good performance in terms of recognition errors, parallel implementation, and noise characteristics.

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An Evaluation of the Second-order Approximation Method for Engineering Optimization (최적설계시 이차근사법의 수치성능 평가에 관한 연구)

  • 박영선;박경진;이완익
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.16 no.2
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    • pp.236-247
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    • 1992
  • Optimization has been developed to minimize the cost function while satisfying constraints. Nonlinear Programming method is used as a tool for the optimization. Usually, cost and constraint function calculations are required in the engineering applications, but those calculations are extremely expensive. Especially, the function and sensitivity analyses cause a bottleneck in structural optimization which utilizes the Finite Element Method. Also, when the functions are quite noisy, the informations do not carry out proper role in the optimization process. An algorithm called "Second-order Approximation Method" has been proposed to overcome the difficulties recently. The cost and constraint functions are approximated by the second-order Taylor series expansion on a nominal points in the algorithm. An optimal design problem is defined with the approximated functions and the approximated problem is solved by a nonlinear programming numerical algorithm. The solution is included in a candidate point set which is evaluated for a new nominal point. Since the functions are approximated only by the function values, sensitivity informations are not needed. One-dimensional line search is unnecessary due to the fact that the nonlinear algorithm handles the approximated functions. In this research, the method is analyzed and the performance is evaluated. Several mathematical problems are created and some standard engineering problems are selected for the evaluation. Through numerical results, applicabilities of the algorithm to large scale and complex problems are presented.presented.

A Development of Two-Point Reciprocal Quadratic Approximation Mehtod for Configuration Optimization of Discrete Structures (불연속구조물의 배치최적설계를 위한 이점역이차근사법의 개발)

  • Park, Yeong-Seon;Im, Jae-Mun;Yang, Cheol-Ho;Park, Gyeong-Jin
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.20 no.12
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    • pp.3804-3821
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    • 1996
  • The configuration optimization is a structural optimization method which includes the coordinates of a structure as well as the sectional properties in the design variable set. Effective reduction of the weight of discrete structures can be obrained by changing the geometry while satisfying stress, Ei;er bickling, displacement, and frequency constraints, etc. However, the nonlinearity due to the configuration variables may cause the difficulties of the convergence and expensive computational cost. An efficient approximation method for the configuration optimization has been developed to overcome the difficulties. The method approximates the constraint functions based onthe second-order Taylor series expansion with reciprocal design variables. The Hessian matrix is approzimated from the information on previous design points. The developed algotithms are coded and the examples are solved.