• Title/Summary/Keyword: Dynamic shim

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Global torque optimization of redundant manipulator using dynamic programming

  • Shim, Ick-Chan;Yoon, Yong-San
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.811-814
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    • 1997
  • In this paper, the torque optimization of a kinematically redundant manipulator for minimizing the torque demands is discussed. The minimum torque solution based on a local optimization has been known to encounter the instability problem and then the global torque optimization was suggested as one of the alternatives. Herein, by adopting the infinity-norm rather than the 2-norm for the magnitude of torques, we are to propose a new cost function more advantageous to the avoidance of torque limits. By the way, a solution to the global torque optimization formulated with the new cost function can not be obtained by the previous methods due to their difficulties such as inability to treat discontinuous cost functions and various constraints on the joint variables. Thus, to overcome those deficiencies, we are developing a new approach using the dynamic programming. The effectiveness of the proposed method is shown through simulation examples for a 3-link planar redundant manipulator.

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COMMON FIXED POINTS FOR COMPATIBLE MAPPINGS OF TYPE (P) AND AN APPLICATION IN DYNAMIC PROGRAMMING

  • Liu, Zeqing;Guo, Zhenyu;Kang, Shin-Min;Shim, Soo-Hak
    • Journal of applied mathematics & informatics
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    • 제26권1_2호
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    • pp.61-73
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    • 2008
  • In this paper common fixed point theorems dealing with compatible mappings of type (P) are established. As a application, the existence and uniqueness of common solution for a system of functional equations arising in dynamic programming is given. The results presented in this paper improve, generalize and unify the corresponding results in this field.

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강화학습법을 이용한 유역통합 저수지군 운영 (Basin-Wide Multi-Reservoir Operation Using Reinforcement Learning)

  • 이진희;심명필
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2006년도 학술발표회 논문집
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    • pp.354-359
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    • 2006
  • The analysis of large-scale water resources systems is often complicated by the presence of multiple reservoirs and diversions, the uncertainty of unregulated inflows and demands, and conflicting objectives. Reinforcement learning is presented herein as a new approach to solving the challenging problem of stochastic optimization of multi-reservoir systems. The Q-Learning method, one of the reinforcement learning algorithms, is used for generating integrated monthly operation rules for the Keum River basin in Korea. The Q-Learning model is evaluated by comparing with implicit stochastic dynamic programming and sampling stochastic dynamic programming approaches. Evaluation of the stochastic basin-wide operational models considered several options relating to the choice of hydrologic state and discount factors as well as various stochastic dynamic programming models. The performance of Q-Learning model outperforms the other models in handling of uncertainty of inflows.

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스토캐스틱 시간지연 시스템을 위한 동적 출력궤환 제어기 설계 (Dynamic Output-Feedback Controller Design for Stochastic Time-Delay Systems)

  • 최현철;정진우;심형보;서진헌
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 학술대회 논문집 정보 및 제어부문
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    • pp.462-463
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    • 2008
  • This paper proposes a method for dynamic output-feedback controller design for stochastic time-delay systems. Based on recent results on time-delay systems control, a tractable and delay-dependent design condition is proposed, which provides a dynamic output-feedback controller to render the closed-loop stochastic time-delay systems to be asymptotically stable in the mean-square sense. The feasibility problem of the proposed condition is recast into a cone complementarity problem. An algorithm adopting cone complementarity linearization is presented to solve the resulting problem.

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Solid State Dynamic Nuclear Polarization of 1H Nuclear Spins at 0.3 T and 4.2 K

  • Shim, Jeong Hyun
    • 한국자기공명학회논문지
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    • 제21권4호
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    • pp.114-118
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    • 2017
  • Here, I report solid state Dynamic Nuclear Polarization (DNP) of $^1H$ nuclear spins at 0.3 T and 4.2 K. The DNP polarizer was developed based on a commercial X-band Electron Spin Resonance (ESR) modified for DNP, in combination with a NMR console and a liquid-Helium cryostat. By detuning magnetic field, DNP spectrum was measured to find the optimal condition. At +3 mT detuned from on-resonance field, $^1H$ NMR signal of 60:40 glycerol/water frozen solution doped with 20 mM perdeuterated-Tempone was amplified 43 times. The $^1H$ spin polarization obtained at 4.2 K is over 3100 times higher than that at 300 K. The width of the DNP spectrum, which is five times broader than ESR spectrum, is inconsistent with solid effect or thermal mixing, and presumably suggests a different DNP mechanism.

Multiprocess Dynamic Survival Models with Numbers of Deaths

  • Joo Yong Shim;Joong Kweon Sohn;Sang Gil Kang
    • Journal of the Korean Statistical Society
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    • 제25권4호
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    • pp.567-576
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    • 1996
  • The multiprocess dynamic survival model is proposed for the application of the regression model on the analysis of survival data with time-varying effects of covariates : where the survival data consists of numbers of deaths at certain time-points. The algorithm for the recursive estimation of a time-varying parameter vector is suggested. Also the algorithm of forecasting of numbers of deaths of each group in the next time interval based on the information gathered until the end of current time interval is suggested.

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측정 잡음을 고려한 저차의 동적출력궤환 제어기 설계 (Low-Order Dynamic Output Feedback Controller Design Against Measurement Noise)

  • 손영익;조남훈;심형보
    • 전기학회논문지
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    • 제56권2호
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    • pp.383-388
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    • 2007
  • This paper considers a low-order dynamic output feedback controller design problem. Since the proposed control law inherently has a low-pass filter property, it can alleviate the mal-effects of the sensor noise without additional filter designs. Frequency domain analysis shows the characteristics of the proposed control law against measurement noise. The effectiveness of the proposed control law is illustrated by numerical simulations with a rotary inverted pendulum and a convey-crane. Using only one integrator the proposed control law has the advantage to the stabilization problem with sensor noise as well as it can successfully replace the measurements of derivative terms in a state feedback control law.

Dynamic Monte Carlo transient analysis for the Organization for Economic Co-operation and Development Nuclear Energy Agency (OECD/NEA) C5G7-TD benchmark

  • Shaukat, Nadeem;Ryu, Min;Shim, Hyung Jin
    • Nuclear Engineering and Technology
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    • 제49권5호
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    • pp.920-927
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    • 2017
  • With ever-advancing computer technology, the Monte Carlo (MC) neutron transport calculation is expanding its application area to nuclear reactor transient analysis. Dynamic MC (DMC) neutron tracking for transient analysis requires efficient algorithms for delayed neutron generation, neutron population control, and initial condition modeling. In this paper, a new MC steady-state simulation method based on time-dependent MC neutron tracking is proposed for steady-state initial condition modeling; during this process, prompt neutron sources and delayed neutron precursors for the DMC transient simulation can easily be sampled. The DMC method, including the proposed time-dependent DMC steady-state simulation method, has been implemented in McCARD and applied for two-dimensional core kinetics problems in the time-dependent neutron transport benchmark C5G7-TD. The McCARD DMC calculation results show good agreement with results of a deterministic transport analysis code, nTRACER.