• 제목/요약/키워드: uncertain dynamic system

검색결과 154건 처리시간 0.026초

확률적 비선형 동적계의 해석에 관한 연구 (A Study on the Analysis of Stochastic Nonlinear Dynamic System)

  • 남성현;김호룡
    • 대한기계학회논문집
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    • 제19권3호
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    • pp.697-704
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    • 1995
  • The dynamic characteristics of a system can be critically influenced by system uncertainty, so the dynamic system must be analyzed stochastically in consideration of system uncertainty. This study presents the stochastic model of a nonlinear dynamic system with uncertain parameters under nonstationary stochastic inputs. And this stochastic system is analyzed by a new stochastic process closure method and moment equation method. The first moment equation is numerically evaluated by Runge-Kutta method and the second moment equation is numerically evaluated by stochastic process closure method, 4th cumulant neglect closure method and Runge-Kutta method. But the first and the second moment equations are coupled each other, so this equations are approximately evaluated by a iterative method. Finally the accuracy of the present method is verified by Monte Carlo simulation.

THE ROBUST CONTROLLER DESIGN FOR UNCERTAIN MULTIVARIABLE SYSTEM USING SWITCHING DYNAMICS

  • Park, Gwi-Tae;Kuo, Chun-Ping;Kim, Dong-Sik;Lim, Sung-Jun
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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    • pp.924-930
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    • 1989
  • This paper presents the design of simple robust controller for a class of uncertain multivariable systems. We introduce switching dynamics instead of switching logics unlike variable structure control scheme. Also, we can construct the continuous control law from this switching dynamics and consequently remove the chattering motion. The dynamic equations of the range-space of a switching surface matrix C and uniform ultimate boundedness in the presence of parameter uncertainties are described mathematically.

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동적 신경망에 기초한 불확실한 로봇 시스템의 적응 최적 학습제어기 (DNN-Based Adaptive Optimal Learning Controller for Uncertain Robot Systems)

  • 정재욱;국태용;이택종
    • 전자공학회논문지S
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    • 제34S권6호
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    • pp.1-10
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    • 1997
  • This paper presents an adaptive optimal learning controller for uncertian robot systems which makes use fo simple DNN(dynamic neural network) units to estimate uncertain parameters and learn the unknown desired optimal input. With the aid of a lyapunov function, it is shown that all that error signals in the system are bounded and the robot trajectory converges to the desired one globally exponentially. The effectiveness of the proposed controller is hsown by applying the controller to a 2-DOF robot manipulator.

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Dynamics Identification and Robust Control Performance Evaluation of Towing Rope under Rope Length Variation

  • Tran, Anh-Minh D.;Kim, Young-Bok
    • 동력기계공학회지
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    • 제20권2호
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    • pp.58-65
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    • 2016
  • Lately, tugboats are widely used to maneuver vessels by pushing or towing them where tugboats use rope. In order to correctly control the motion of tugboat and towed vessel, the dynamics of the towline would be well identified. In real application environment, the towing rope length changes and the towing load is not constant due to the various sizes of towed vessel. And there are many ropes made by many types of materials. It means that it is not easy to obtain rope dynamics, such that it is too difficult to satisfy the given control purpose by designing control system. Thus real time identification or adaptive control system design method may be a solution. However it is necessary to secure sufficient information about rope dynamics to obtain desirable control performance. In this paper, the authors try to have several rope dynamic models by changing the rope length to consider real application conditions. Among them, a representative model is selected and the others are considered as uncertain models which are considered in control system design. The authors design a robust control to cope with strong uncertain and nonlinear property included in the real plant. The designed control system based on robust control framework is evaluated by simulation.

불확실 이산 시스템을 위한 외란관측기와 적분 동특성형 슬라이딩 면을 갖는 새로운 둔감한 이산 적분 정적 출력 궤환 가변구조제어기 (A New Robust Discrete Integral Static Output Feedback Variable Structure Controller with Disturbance Observer and Integral Dynamic-Type Sliding Surface for Uncertain Discrete Systems)

  • 이정훈
    • 전기학회논문지
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    • 제59권7호
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    • pp.1289-1294
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    • 2010
  • In this paper, a new discrete integral static output feedback variable structure controller based on the a new integral dynamic-type sliding surface and output feedback discrete version of the disturbance observer is suggested for the control of uncertain linear systems. The reaching phase is completely removed by introducing a new proposed integral dynamic-type sliding surface. The output feedback discrete version of disturbance observer is presented for effective compensation of uncertainties and disturbance. A corresponding control with disturbance compensation is selected to guarantee the quasi sliding mode on the predetermined integral dynamic-type sliding surface for guaranteeing the designed output in the integral dynamic-type sliding surface from any initial condition for all the parameter variations and disturbances. Using discrete Lyapunov function, the closed loop stability and the existence condition of the quasi sliding mode is proved. Finally, an illustrative example is presented to show the effectiveness of the algorithm.

An Identification of the Hydraulic Motion Simulator Using Modified Signal Compression Method and Its Application

  • Park, Min-Kyu;Lee, Min-Cheol;Go, Seok-Jo
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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    • pp.133-136
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    • 1999
  • Many researches on the identification of a system have been carried out using a least square method, an adaptive filter, and so on. However, it is difficult to apply these methods in a nonlinear system. In the case of a nonlinear system, it is known that the signal compression method is able to estimate uncertain parameters of linear element in a nonlinear system because it is able to separate linear element and nonlinear element in a nonlinear system. However, the signal compression method cannot be applied to a motion simulator because actuators of the simulator is single-rod cylinders which includes expansion and compression dynamic properties. Therefore, this paper proposes a modified signal compression method which is able to estimate uncertain parameters of the motion simulator dynamics. The dynamic properties of this system are identified by separating expansion and compression properties when applying the signal compression method. And then, the identified parameters are applied to design a sliding mode controller for the simulator. The performance of the designed sliding mode controller is evaluated experimentally.

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불확실한 비선형 계통에 대한 SPR 조건이 필요 없는 적응 퍼지 관측기 (Adaptive Fuzzy Observer without SPR Condition for Uncertain Nonlinear Systems)

  • 박장현;김성환
    • 전기전자학회논문지
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    • 제7권2호
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    • pp.156-165
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    • 2003
  • 본 논문은 불확실한 비선형 계통에 대해서 강인한 적응 퍼지 관측기를 설계하는 방법을 제시한다. 새로 제시하는 관측기는 관측기 설계시 관측오차의 동특성식이 SPR (strictly positive real)이어야 한다는 조건이 불필요하다. 또한 불확실한 항에 대한 유계상수도 추정하는 알고리듬을 사용하여 강인항의 이득값을 설계자가 미리 결정할 필요가 없게 된다. 설계된 관측기를 포함한 전체 폐루프 계통에 대해서 리아프노브 안정도를 증명하였으며 관측오차를 포함한 계통의 모든 신호들의 반전역적 유계(semi-global uniform ultimate boundedness)임을 증명하였다. 이론적으로 도출된 결과를 mass-spring-damper 계통에 대한 모의실험을 수행하여 제안된 관측기의 효율성과 성능을 보였다.

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Dynamic behavior of the one-stage gear system with uncertainties

  • Beyaoui, M.;Guerine, A.;Walha, L.;Hami, A. El;Fakhfakh, T.;Haddar, M.
    • Structural Engineering and Mechanics
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    • 제58권3호
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    • pp.443-458
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    • 2016
  • In this paper, we propose a method for taking into account uncertainties based on the projection on polynomial chaos. Due to the manufacturing and assembly errors, uncertainties in material and geometric properties, the system parameters including assembly defect, damping coefficients, bending stiffness and traction-compression stiffness are uncertain. The proposed method is used to determine the dynamic response of a one-stage spur gear system with uncertainty associated to gear system parameters. An analysis of the effect of these parameters on the one stage gear system dynamic behavior is then treated. The simulation results are obtained by the polynomial chaos method for dynamic analysis under uncertainty. The proposed method is an efficient probabilistic tool for uncertainty propagation. The polynomial chaos results are compared with Monte Carlo simulations.

불확실한 이동 로봇에 대한 RBFN 기반 적응 추종 제어기의 설계 (Design of an RBFN-based Adaptive Tracking Controller for an Uncertain Mobile Robot)

  • 신진호;백운보
    • 제어로봇시스템학회논문지
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    • 제20권12호
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    • pp.1238-1245
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    • 2014
  • This paper proposes an RBFN-based adaptive tracking controller for an electrically driven mobile robot with parametric uncertainties and external disturbances. A mobile robot model considered in this paper includes all models of the robot body and actuators with uncertain kinematic and dynamic parameters, and uncertain frictions and external disturbances. The proposed controller consists of an RBFN(Radial Basis Function Network) and a robust adaptive controller. The presented RBFN is used to approximate unknown nonlinear robot dynamic functions. The proposed controller is adjusted by the adaptation laws obtained through the Lyapunov stability analysis. The proposed control scheme does not a priori need the accurate knowledge of all parameters in the robot kinematics, robot dynamics and actuator dynamics. Also, nominal parameter values are not required in the controller. The global stability of the closed-loop robot control system is guaranteed using the Lyapunov stability theory. Simulation results show the validity and robustness of the proposed control scheme.

Dependence assessment in human reliability analysis under uncertain and dynamic situations

  • Gao, Xianghao;Su, Xiaoyan;Qian, Hong;Pan, Xiaolei
    • Nuclear Engineering and Technology
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    • 제54권3호
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    • pp.948-958
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    • 2022
  • Since reliability and security of man-machine system increasingly depend on reliability of human, human reliability analysis (HRA) has attracted a lot of attention in many fields especially in nuclear engineering. Dependence assessment among human tasks is a important part in HRA which contributes to an appropriate evaluation result. Most of methods in HRA are based on experts' opinions which are subjective and uncertain. Also, the dependence influencing factors are usually considered to be constant, which is unrealistic. In this paper, a new model based on Dempster-Shafer evidence theory (DSET) and fuzzy number is proposed to handle the dependence between two tasks in HRA under uncertain and dynamic situations. First, the dependence influencing factors are identified and the judgments on the factors are represented as basic belief assignments (BBAs). Second, the BBAs of the factors that varying with time are reconstructed based on the correction BBA derived from time value. Then, BBAs of all factors are combined to gain the fused BBA. Finally, conditional human error probability (CHEP) is derived based on the fused BBA. The proposed method can deal with uncertainties in the judgments and dynamics of the dependence influencing factors. A case study is illustrated to show the effectiveness and the flexibility of the proposed method.