• Title/Summary/Keyword: approximation technique

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THREE-POINT BOUNDARY VALUE PROBLEMS FOR HIGHER ORDER NONLINEAR FRACTIONAL DIFFERENTIAL EQUATIONS

  • Khan, Rahmat Ali
    • Journal of applied mathematics & informatics
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    • v.31 no.1_2
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    • pp.221-228
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    • 2013
  • The method of upper and lower solutions and the generalized quasilinearization technique is developed for the existence and approximation of solutions to boundary value problems for higher order fractional differential equations of the type $^c\mathcal{D}^qu(t)+f(t,u(t))=0$, $t{\in}(0,1),q{\in}(n-1,n],n{\geq}2$ $u^{\prime}(0)=0,u^{\prime\prime}(0)=0,{\ldots},u^{n-1}(0)=0,u(1)={\xi}u({\eta})$, where ${\xi},{\eta}{\in}(0,1)$, the nonlinear function f is assumed to be continuous and $^c\mathcal{D}^q$ is the fractional derivative in the sense of Caputo. Existence of solution is established via the upper and lower solutions method and approximation of solutions uses the generalized quasilinearization technique.

Intelligent Sliding Mode Control for Robots Systems with Model Uncertainties (모델 불확실성을 가지는 로봇 시스템을 위한 지능형 슬라이딩 모드 제어)

  • Yoo, Sung-Jin;Choi, Yoon-Ho;Park, Jin-Bae
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.10
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    • pp.1014-1021
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    • 2008
  • This paper proposes an intelligent sliding mode control method for robotic systems with the unknown bound of model uncertainties. In our control structure, the unknown bound of model uncertainties is used as the gain of the sliding controller. Then, we employ the function approximation technique to estimate the unknown nonlinear function including the width of boundary layer and the uncertainty bound of robotic systems. The adaptation laws for all parameters of the self-recurrent wavelet neural network and those for the reconstruction error compensator are derived from the Lyapunov stability theorem, which are used for an on-line control of robotic systems with model uncertainties and external disturbances. Accordingly, the proposed method can not only overcome the chattering phenomenon in the control effort but also have the robustness regardless of model uncertainties and external disturbances. Finally, simulation results for the five-link biped robot are included to illustrate the effectiveness of the proposed method.

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 Seat Allocation Problem for Package Tour Groups in Airlines (항공사 패키지 여행 단체수요의 좌석할당 문제)

  • Song, Yoon-Sook;Lee, Hwi-Young;Yoon, Moon-Gil
    • Korean Management Science Review
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    • v.25 no.1
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    • pp.93-106
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    • 2008
  • This study is focused on the problem of seat allocation for group travel demand in airlines. We first explain the characteristic of group demand and its seat allocation process. The group demand in air travel markets can be classified into two types : incentive and package groups. Allocating seats for group demand depends on the types of group demand and the relationship between airlines and travel agents. In this paper we concentrate on the package group demand and develop an optimization model for seat allocation on the demand to maximize the total revenue. With some assumptions on the demand distribution and the linear approximation technique, we develop a mixed IP model for solving our problem optimally. From the computational experiments, we can find our optimization model can be applied well for real-world application.

Decentralized Adaptive Control for Nonlinear Systems with Time-Delayed Interconnections: Intelligent Approach (시간 지연 상호 연계를 가진 비선형 시스템의 분산 적응 제어: 지능적인 접근법)

  • Yoo, Sung-Jin;Park, Jin-Bae
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.4
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    • pp.413-419
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    • 2009
  • A decentralized adaptive control method is proposed for large-scale systems with unknown time-delayed nonlinear interconnections unmatched in control inputs. It is assumed that the time-delayed interaction terms are bounded by unknown nonlinear bounding functions. The nonlinear bounding functions and uncertain nonlinear functions of large-scale systems are compensated by the function approximation technique using neural networks. The dynamic surface control method is extended to design the proposed memoryless local controller for each subsystem of uncertain nonlinear large-scale time delay systems. Therefore, although the interconnected systems consist of a large number of subsystems, the proposed controller can be designed simply. We prove that all the signals in the total closed-loop system are semiglobally uniformly bounded and the control errors converge to an adjustable neighborhood of the origin. Finally, an example is given to demonstrate the effectiveness and applicability of the proposed scheme.

A Study on Simple Adaptive Control of Flexible-Joint Robots Considering Motor Dynamics (모터 동역학식을 고려한 유연 연결 로봇의 간단한 적응 제어에 관한 연구)

  • Yoo, Sung-Jin;Choi, Yoon-Ho;Park, Jin-Bae
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.11
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    • pp.1103-1109
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    • 2008
  • Since the flexible joint robots with motor dynamics are represented by the fifth-order nonlinear sγstem, it is difficult and complex to design the controller for electrically driven flexible-joint (EDFJ) robots. In this paper, we propose a simple adaptive control method to solve this problem. It is assumed that the model uncertainties of the robots dynamics, joint flexibility, and motor dynamics are unknown. For the simple control design, the dynamic surface design method is applied, and all uncertainties in the robot and motor dynamics are compensated by using the adaptive function approximation technique. It is proved that all signals in the controlled closed-loop system are uniformly ultimately bounded. Simulation results for three-link EDFJ manipulators are provided to validate the effectiveness of the proposed control system.

Robust H$_{\infty}$ Control Method for Bilinear Systems

  • Kim, Beom-Soo;Lim, Myo-Taeg
    • International Journal of Control, Automation, and Systems
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    • v.1 no.2
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    • pp.171-177
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    • 2003
  • In this paper, we investigate a robust $H_{\infty}$ state feedback control technique for continuous time bilinear systems with an additive disturbance input. The nonlinear robust $H_{\infty}$control for bilinear systems requires a solution to the state dependent algebraic Riccati equation (SDARE). We present a new robust $H_{\infty}$control technique based on the successive approximation method for solving the SDARE by converting bilinear systems into time-varying linear systems. The proposed control method guarantees robust stability for closed loop bilinear systems. The proposed algorithm is verified by numerical examples.

Piece-wise linear estimation of mechanical properties of materials with neural networks

  • Shin, Inho
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10b
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    • pp.181-186
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    • 1992
  • Many real-world problems are concerned with estimation rather than classification. This paper presents an adaptive technique to estimate the mechanical properties of materials from acoustoultrasonic waveforms. This is done by adapting a piece-wise linear approximation technique to a multi-layered neural network architecture. The piece-wise linear approximation network (PWLAN) finds a set of connected hyperplanes that fit all input vectors as close as possible. A corresponding architecture requires only one hidden layer to estimate any curve as an output pattern. A learning rule for PWLAN is developed and applied to the acousto-ultrasonic data. The efficiency of the PWLAN is compared with that of classical backpropagation network which uses generalized delta rule as a learning algorithm.

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Design of Initial Billet using the Artificial Neural Network for a Hot Forged Product (신경망을 이용한 열간단조품의 초기 소재 설계)

  • 김동진;김벙민;최재찬
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1995.04b
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    • pp.198-203
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    • 1995
  • In the paper, we have proposed a new technique to detemine the initial billet for the forged products using a function approximation in neural network. A three-layer neural network is used and a back propagation algorithm is employed totrain the network. An optimal billet which satisfied the forming limitation, minimum of incomplete filling in the die cavity, load and energyas well as more uniform distribution of effective strain, is determined by applying the ability of function approximation of te neural network. The amount of incomplete filling in the die, load and forming energyas well as effective strain are measured by the rigid-plastic finite element method. The new technique is applied tofind the optimal billet size for the axisymmetric rib-web product in hot forging. This would reduce the number of finite element simulation for determing the optimal billet of forging products, further it is usefully adapted to physical modeling for the forging design.

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Maximum penalized likelihood estimation for a stress-strength reliability model using complete and incomplete data

  • Hassan, Marwa Khalil
    • Communications for Statistical Applications and Methods
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    • v.25 no.4
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    • pp.355-371
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    • 2018
  • The two parameter negative exponential distribution has many practical applications in queuing theory such as the service times of agents in system, the time it takes before your next telephone call, the time until a radioactive practical decays, the distance between mutations on a DNA strand, and the extreme values of annual snowfall or rainfall; consequently, has many applications in reliability systems. This paper considers an estimation problem of stress-strength model with two parameter negative parameter exponential distribution. We introduce a maximum penalized likelihood method, Bayes estimator using Lindley approximation to estimate stress-strength model and compare the proposed estimators with regular maximum likelihood estimator for complete data. We also introduce a maximum penalized likelihood method, Bayes estimator using a Markov chain Mote Carlo technique for incomplete data. A Monte Carlo simulation study is performed to compare stress-strength model estimates. Real data is used as a practical application of the proposed model.