• 제목/요약/키워드: Dynamic Adaptive Model

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Simulation of Vehicle-Track-Bridge Dynamic Interaction by Nonlinear Hertzian Contact Spring and Displacement Constraint Equations (비선형 헤르쯔 접촉스프링과 변위제한조건식의 적용에 의한 차량-궤도-교량 동적상호작용 수치해석기법)

  • Chung Keun-Young;Lee Sung-Uk;Min Kyung-Ju
    • Proceedings of the KSR Conference
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    • 2005.11a
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    • pp.191-196
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    • 2005
  • In this study, to describe vehicle-track-bridge dynamic interaction phenomena with 1/4 vehicle model, nonlinear Hertzian contact spring and nonlinear contact damper are introduced. In this approach external loads acting on 1/4 vehicle model are self weight of vehicle and geometry information of running surface. The constraint equation on contact surface is implemented by Penalty method. Also, to improve the numerical stability and to maintain accuracy of solution, the artificial damper and the reaction from constraint violation are introduced. A nonlinear time integration method, in this study, Newmark method is adopted for both equations of vehicles and structure. And to reduce the error caused by inadequate time step size, adaptive time-stepping technique is partially introduced. As the nonlinear Hertzian contact spring has no resistance to tensile force, the bouncing phenomena of wheelset can be described. Thus, it is expected that more versatile dynamic interaction phenomena can be described by this approach and it can be applied to various railway dynamic problems.

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The study on the efficient Identification Model of Nonlinear dynamical system using Neural Networks (신경회로망을 이용한 비선형 동적인 시스템의 효과적인 인식모델에 관한 연구)

  • 강동우;이상배
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1995.10b
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    • pp.233-242
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    • 1995
  • In this paper, we introduce the identification model of dynamic system using the neural networks, We propose two identification models. The output of the parallel identification model is a linear combination of its past values as well as those of the input. The series-parallel model is a linear combination of the past values in the input and output of the plant. To generate stable adaptive laws, we prove that the series-parallel model is found to be proferable.

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Trajectory Tracking Control of a Real Redundant Manipulator of the SCARA Type

  • Urrea, Claudio;Kern, John
    • Journal of Electrical Engineering and Technology
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    • v.11 no.1
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    • pp.215-226
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    • 2016
  • Modeling, control and implementation of a real redundant robot with five Degrees Freedom (DOF) of the SCARA (Selective Compliant Assembly Robot Arm) manipulator type is presented. Through geometric methods and structural and functional considerations, the inverse kinematics for redundant robot can be obtained. By means of a modification of the classical sliding mode control law through a hyperbolic function, we get a new algorithm which enables reducing the chattering effect of the real actuators, which together with the learning and adaptive controllers, is applied to the model and to the real robot. A simulation environment including the actuator dynamics is elaborated. A 5 DOF robot, a communication interface and a signal conditioning circuit are designed and implemented for feedback. Three control laws are executed in: a simulation structure (together with the dynamic model of the SCARA type redundant manipulator and the actuator dynamics) and a real redundant manipulator of the SCARA type carried out using MatLab/Simulink programming tools. The results, obtained through simulation and implementation, were represented by comparative curves and RMS indices of the joint errors, and they showed that the redundant manipulator, both in the simulation and the implementation, followed the test trajectory with less pronounced maximum errors using the adaptive controller than the other controllers, with more homogeneous motions of the manipulator.

Dynamic Adaptive Model based on Probabilistic Distribution Functions and User's Profile for Web Media Systems (웹 미디어 시스템을 위한 확률 분포 함수와 사용자 프로파일에 기반 한 동적 적응 모델)

  • Baek, Yeong-Tae;Lee, Se-Hoon
    • The Journal of Korean Association of Computer Education
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    • v.6 no.1
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    • pp.29-39
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    • 2003
  • In this paper we proposed dynamic adaptive model based on discrete probabilistic distribution functions and user's profile for web media systems(web based hypermedia systems). The model represented that the application domain is modelled using a weighted direct graph and the user's behaviour is modelled using a probabilistic approach that dynamically constructs a discrete probability distribution functions. The proposed probabilistic interpretation of the web media structure is used to characterize latent properties of the user's behaviour, which can be captured by tracking user's browsing activity. Using that distribution the system attempts to assign the user to the best profile that fits user's expectations.

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Exploring Knowledge Processing in a Social Complex Adaptive Organization : Wikipedia through the Lens of the LIFE Model

  • Faucher, Jean-Baptiste P.L.;Everett, Andre M.;Lawson, Rob
    • Journal of Information Technology Applications and Management
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    • v.18 no.1
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    • pp.15-39
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    • 2011
  • A deeper understanding of how organizations behave as social complex adaptive systems is needed. In this paper we demonstrate how the Leadership Invigorating Flows of Energies model can help with this understanding. The model highlights the role of emergent leadership as a force encouraging the creation, diffusion, and utilization of knowledge through self-organizing mechanisms. We illustrate our approach by examining Wikipedia and show how it can be described as a social CAS. Our analysis of Wikipedia describes how emerging intrapreneurship behaviors result in dynamic flows of knowledge and self-organizing feedback mechanisms across the organization. We provide implications for organization studies and present evidence to support claims made by advocates of complexity theory. We conclude by proposing that Wikipedia can be seen as a new form of organization, and finish with a brief note highlighting a possible way forward.

Design of a real time adaptive controller for industrial robot using TMS320C31 chip (TMS320C31칩을 사용한 산엽용 로보트의 실시간 적응 제어기 설계)

  • Han, S.H.;Kim, Y.T.;Lee, M.H.;Kim, S.K.;Kim, J.O.
    • Journal of the Korean Society for Precision Engineering
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    • v.13 no.10
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    • pp.94-104
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    • 1996
  • This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C31) for robotic manpulators to achieve accurate trajectory tracking by the joint angles Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed contorl scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Morever, this scheme does not require an accurate dynamic modeling nor values of manpipulator parameters and payload. Performance of the adaptive controller is illustated by simulation and experimental results for a SCARA robot.

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An Improved Adaptive Background Mixture Model for Real-time Object Tracking based on Background Subtraction (배경 분리 기반의 실시간 객체 추적을 위한 개선된 적응적 배경 혼합 모델)

  • Kim Young-Ju
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.6 s.38
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    • pp.187-194
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    • 2005
  • The background subtraction method is mainly used for the real-time extraction and tracking of moving objects from image sequences. In the outdoor environment, there are many changeable environment factors such as gradually changing illumination, swaying trees and suddenly moving objects , which are to be considered for an adaptive processing. Normally, GMM(Gaussian Mixture Model) is used to subtract the background by considering adaptively the various changes in the scenes, and the adaptive GMMs improving the real-time Performance were Proposed and worked. This paper, for on-line background subtraction, employed the improved adaptive GMM, which uses the small constant for learning rate a and is not able to speedily adapt the suddenly movement of objects, So, this paper Proposed and evaluated the dynamic control method of a using the adaptive selection of the number of component distributions and the global variances of pixel values.

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Substructural parameters and dynamic loading identification with limited observations

  • Xu, Bin;He, Jia
    • Smart Structures and Systems
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    • v.15 no.1
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    • pp.169-189
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    • 2015
  • Convergence difficulty and available complete measurement information have been considered as two primary challenges for the identification of large-scale engineering structures. In this paper, a time domain substructural identification approach by combining a weighted adaptive iteration (WAI) algorithm and an extended Kalman filter method with a weighted global iteration (EFK-WGI) algorithm was proposed for simultaneous identification of physical parameters of concerned substructures and unknown external excitations applied on it with limited response measurements. In the proposed approach, according to the location of the unknown dynamic loadings and the partially available structural response measurements, part of structural parameters of the concerned substructure and the unknown loadings were first identified with the WAI approach. The remaining physical parameters of the concerned substructure were then determined by EFK-WGI basing on the previously identified loadings and substructural parameters. The efficiency and accuracy of the proposed approach was demonstrated via a 20-story shear building structure and 23 degrees of freedom (DOFs) planar truss model with unknown external excitation and limited observations. Results show that the proposed approach is capable of satisfactorily identifying both the substructural parameters and unknown loading within limited iterations when both the excitation and dynamic response are partially unknown.

Application of an Adaptive Step-size Algorithm to the Power System Model of Dispatcher Training Simulator (적응 간격 크기 셈법을 이용한 급전운영자 훈련 프로그램 용 전력계통 시뮬레이터 개발)

  • Hwang, Pyeong-Ik;Ahn, Seon-Ju;Moon, Seung-Il;Yoon, Yong-Tae;Hur, Seong-Il
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.59 no.3
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    • pp.492-498
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    • 2010
  • Since it is almost impossible to train the dispatchers with real power system, the dispatcher training simulator(DTS) is used for the training. Among various components of the DTS, the power system model(PSM) emulates the dynamic behavior of the power system to calculate the frequency and voltage. The frequency is calculated from various parameters such as mechanical power of power plants, load, inertia, and the damping of the power system. In the PSM, the power plants are modeled as differential equations, so the mechanical power of the power plants are calculated by the numerical methods. Conventionally, the fixed step-size algorithm has been used in the PSM, however it has some drawbacks. This paper develops the prototype PSM using the Matlab, and analyzes the problems of the fixed step-size algorithm by comparing the results with those of PSCAD simulation. In order to overcome the limitations, this paper proposes a modified frequency calculation method using the adaptive step-size algorithm. From the simulation using the proposed method, it is verified that the accuracy of frequency calculation increases substantially while the simulation time is not greatly increased.

Robust Decentralized Adaptive Controller for Trajectory Tracking Control of Uncertain Robotic Manipulators (비중앙 집중식 강성 적응 제어법을 통한 산업용 로봇 궤도추적제어)

  • 유삼상
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.30 no.4
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    • pp.329-340
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    • 1994
  • This paper presents a dynamic compensation methodology for robust trajectory tracking control of uncertain robot manipulators. To improve tracking performance of the system, a full model-based feedforward compensation with continuous VS-type robust control is developed in this paper(i.e,. robust decentralized adaptive control scheme). Since possible bounds of uncertainties are unknown, the adaptive bounds of the robust control is used to directly estimate the uncertainty bounds(instead of estimating manipulator parameters as in centralized adaptive control0. The global stability and robustness issues of the proposed control algorithm have been investigated extensively and rigorously via a Lyapunov method. The presented control algorithm guarantees that all system responses are uniformly ultimately bounded. Thus, it is shown that the control system is evaluated to be highly robust with respect to significant uncertainties.

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