• Title/Summary/Keyword: Dynamic Adaptive Model

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Adaptive Learning System using Real-time Learner Profiling (실시간 학습자 프로파일링을 이용한 적응적 학습 시스템)

  • Yang, Yeong-Wook;Yu, Won-Hee;Lim, Heui-Seok
    • Journal of Digital Convergence
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    • v.12 no.2
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    • pp.467-473
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    • 2014
  • Adaptive learning system means a system that provides adaptively learning materials according to the learning needs of learners. It consists of expert model, instructional model and student model. Expert model is that stores information which is to be taught. Student model stores the data of learning history and learning information of students. Instructional model provides necessary learning materials for actual leaners. This paper has constructed student model through learner's profile information and instructional model through dynamic scenario construction. After that, We have developed adaptively to provide learning to learners by constructing suitable dynamic scenario based on learners profile information. In the end, satisfaction result about this system showed a high degree of satisfaction and 88%.

Dynamic Modelling and Control of Solid-Oxide Fuel Cell (고체산화 연료전지의 동특성 모델링과 제어)

  • Hyun, Keun-Ho;Son, In-Hwan;Ka, Chul-Hyun
    • Proceedings of the KIEE Conference
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    • 2005.07d
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    • pp.2516-2518
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    • 2005
  • In this paper, the dynamic models of SOFC are suggested. It consists of electrochemical model, thermal model, voltage equation and several loss equations. Control problem on tracking steady voltage by air flow is discussed and an adaptive controller is designed to withstand to the variation of stack current. Simulation is done to prove the solution of control algorithms.

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Lyapunov-based Semi-active Control of Adaptive Base Isolation System employing Magnetorheological Elastomer base isolators

  • Chen, Xi;Li, Jianchun;Li, Yancheng;Gu, Xiaoyu
    • Earthquakes and Structures
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    • v.11 no.6
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    • pp.1077-1099
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    • 2016
  • One of the main shortcomings in the current passive base isolation system is lack of adaptability. The recent research and development of a novel adaptive seismic isolator based on magnetorheological elastomer (MRE) material has created an opportunity to add adaptability to base isolation systems for civil structures. The new MRE based base isolator is able to significantly alter its shear modulus or lateral stiffness with the applied magnetic field or electric current, which makes it a competitive candidate to develop an adaptive base isolation system. This paper aims at exploring suitable control algorithms for such adaptive base isolation system by developing a close-loop semi-active control system for a building structure equipped with MRE base isolators. The MRE base isolator is simulated by a numerical model derived from experimental characterization based on the Bouc-Wen Model, which is able to describe the force-displacement response of the device accurately. The parameters of Bouc-Wen Model such as the stiffness and the damping coefficients are described as functions of the applied current. The state-space model is built by analyzing the dynamic property of the structure embedded with MRE base isolators. A Lyapunov-based controller is designed to adaptively vary the current applied to MRE base isolator to suppress the quake-induced vibrations. The proposed control method is applied to a widely used benchmark base-isolated structure by numerical simulation. The performance of the adaptive base isolation system was evaluated through comparison with optimal passive base isolation system and a passive base isolation system with optimized base shear. It is concluded that the adaptive base isolation system with proposed Lyapunov-based semi-active control surpasses the performance of other two passive systems in protecting the civil structures under seismic events.

An Adaptive Framework for Forecasting Demand and Technological Substitution

  • Kang, Byung-Ryong;Han, Chi-Moon;Yim, Chu-Hwan
    • ETRI Journal
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    • v.18 no.2
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    • pp.87-106
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    • 1996
  • This paper proposes a new model as a framework for forecasting demand and technological substitution, which can accommodate different patterns of technological change. This model, which we named, "Adaptive Diffusion Model", is formalized from a conceptual framework that incorporates several underlying factors determining the market demand for technological products. The formulation of this model is given in terms of a period analysis to improve its explanatory power for dynamic processes in the real world, and is described as a continuous form which approximates a discrete derivation of the model. In order to illustrate the applicability and generality of this model, time-series data of the diffusion rates for some typical products in electronics and telecommunications market have been empirically tested. The results show that the model has higher explanatory power than any other existing model for all the products tested in our study. It has been found that this model can provide a framework which is sufficiently robust in forecasting demand and innovation diffusion for various technological products.

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Robust Control of Robot Manipulator using Self-Tuning Adaptive Control (자기동조 적응제어기법에 의한 로봇 매니퓰레이터의 강인제어)

  • 뱃길호
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 1996.10a
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    • pp.150-155
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    • 1996
  • This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using digital signal processors for robot manipulators. TMS3200C50 is used in implementing real-time adaptive control algorithms provide advanced performance for robot manipulator. In this paper an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm and controller parameters are detemined by the pole-placement method. Performance of self-tuning adaptive controller is illusrated by the simulation and experiment for a SCARA robot.

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Implementation of a Pole-Placement Self-Tuning Adaptive Controller for SCARA Robot Using TMS320C5X Chip (TMS320C5X칩을 사용한 스카라 로봇의 극점 배치 자기동조 적응제어기의 실현)

  • 배길호;한성현
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1996.11a
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    • pp.754-758
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    • 1996
  • This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using Digital signal processors for robot manipulators. TMS320C50 is used in implementing real-time adaptive control algorithms to provide advanced performance for robot manipulator, In this paper, an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. Parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm, and controller parameters we determined by the pole-placement method. Performance of self-tuning adaptive controller is illusrated by the simulation and experiment for a SCARA robot.

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A Study onthe Modelling and control Using GMDH Algorithm (GMDH 알고리즘을 이용한 모델링 및 제어에 관한 연구)

  • 최종헌;홍연찬
    • Journal of the Korean Institute of Intelligent Systems
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    • v.7 no.3
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    • pp.65-71
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    • 1997
  • With the emergence of neural network, there is a revived interest in identification of nonlinear systems. So in this paper, to identify unknown nonlinear systems dynamically we propose DPNN(Dynamic Polynomial Neural Network) using GMDH (Group Method of Data Handling) algorithm. The dynamic system identification using GMDH consists of applying a set of inputloutput data to train the network by dynamically computing the necessary coeffici1:nt sets. Then, MRAC(Mode1 Reference Adaptive Control) is designed to control nonlinear systems using DPNN. In the result, we can see that the modelling and control using DPNN work well by computer simulation.

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Implementation of an adaptive learning control algorithm for robot manipulators (로못 머니퓰레이터를 위한 적응학습제어 알고리즘의 구현)

  • 이형기;최한호;정명진
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10a
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    • pp.632-637
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    • 1992
  • Recently many dynamics control algorithms using robot dynamic equation have been proposed. One of them, Kawato's feedback error learning scheme requires neither an accurate model nor parameter estimation and makes the robot motion closer to the desired trajectory by repeating operation. In this paper, the feedback error learning algorithm is implemented to control a robot system, 5 DOF revolute type movemaster. For this purpose, an actuator dynamic model is constructed considering equivalent robot dynamics model with respect to actuator as well as friction model. The command input acquired from the actuator dynamic model is the sum of products of unknown parameters and known functions. To compute the control algorithm, a parallel processing computer, transputer, is used and real-time computing is achieved. The experiment is done for the three major link of movemaster and its result is presented.

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Design of a Web Based Adaptive Hypermedia System for Education (웹 기반 교육용 적응적 하이퍼미디어 시스템 설계)

  • 백영태
    • Journal of Korea Multimedia Society
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    • v.5 no.1
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    • pp.59-67
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    • 2002
  • In this paper, I discuss the problems of developing web based adaptive hypermedia for education using extensible Markup Language(XML). Adaptive hypermedia systems are capable of altering the Presentation of the contents of the hypermedia on the basis of a dynamic understanding of the individual student. The student profile is contained in a student model, while the knowledge about the domain can be represented in the form of a concept based domain model. Accordingly, I define two different markup languages using XML. The one structures the domain model and the another describes the student model. These language can be easily extended and authored, with the result of obtaining a simple methodology for data structuring in the field of web based educational adaptive hypermedia.

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Application of adaptive mesh refinement technique on digital surface model-based urban flood simulation

  • Dasallas, Lea;An, Hyunuk
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.122-122
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    • 2020
  • Urban flood simulation plays a vital role in national flood early warning, prevention and mitigation. In recent studies on 2-dimensional flood modeling, the integrated run-off inundation model is gaining grounds due to its ability to perform in greater computational efficiency. The adaptive quadtree shallow water numerical technique used in this model implements the adaptive mesh refinement (AMR) in this simulation, a procedure in which the grid resolution is refined automatically following the flood flow. The method discounts the necessity to create a whole domain mesh over a complex catchment area, which is one of the most time-consuming steps in flood simulation. This research applies the dynamic grid refinement method in simulating the recent extreme flood events in Metro Manila, Philippines. The rainfall events utilized were during Typhoon Ketsana 2009, and Southwest monsoon surges in 2012 and 2013. In order to much more visualize the urban flooding that incorporates the flow within buildings and high-elevation areas, Digital Surface Model (DSM) resolution of 5m was used in representing the ground elevation. Results were calibrated through the flood point validation data and compared to the present flood hazard maps used for policy making by the national government agency. The accuracy and efficiency of the method provides a strong front in making it commendable to use for early warning and flood inundation analysis for future similar flood events.

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