• Title/Summary/Keyword: Uncertain Vector

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Comonotonic Uncertain Vector and Its Properties

  • Li, Shengguo;Zhang, Bo;Peng, Jin
    • Industrial Engineering and Management Systems
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    • v.12 no.1
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    • pp.16-22
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    • 2013
  • This paper proposes a new concept of comonotonicity of uncertain vector based on the uncertainty theory. In order to understand the comonotonicity of uncertain vector, some equivalent definitions are presented. Following the proposed concept, some basic properties of comonotonic uncertain vector are investigated. In addition, the operational law is given for calculating the uncertainty distributions of monotone functions of comonotonic uncertain variables. With the help of operational law, the comonotonic uncertain vector is applied to the premium pricing problems. At last, some numerical examples are given to illustrate the application.

Completely Feedback Linearizable Families for Uncertain Nonlinear System (완전 선형화 가능한 미지구조를 가지는 비선형 시스템)

  • Joo, Sung-Jun;Jeon, Hee
    • Proceedings of the KIEE Conference
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    • 1997.07b
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    • pp.422-424
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    • 1997
  • In this paper, we characterize the whole class of vector fields that can be linearized by a given nominal state transformation and a feedback linearizing controller. The necessary and sufficient condition for a given uncertain vector field to be so-called "completely linearizable by the nominal coordinate transformation" is given in terms of Lie Bracket of uncertain vector fields and some suitable vector fields of the nominal system.

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Probabilistic structural damage detection approaches based on structural dynamic response moments

  • Lei, Ying;Yang, Ning;Xia, Dandan
    • Smart Structures and Systems
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    • v.20 no.2
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    • pp.207-217
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    • 2017
  • Because of the inevitable uncertainties such as structural parameters, external excitations and measurement noises, the effects of uncertainties should be taken into consideration in structural damage detection. In this paper, two probabilistic structural damage detection approaches are proposed to account for the underlying uncertainties in structural parameters and external excitation. The first approach adopts the statistical moment-based structural damage detection (SMBDD) algorithm together with the sensitivity analysis of the damage vector to the uncertain parameters. The approach takes the advantage of the strength SMBDD, so it is robust to measurement noise. However, it requests the number of measured responses is not less than that of unknown structural parameters. To reduce the number of measurements requested by the SMBDD algorithm, another probabilistic structural damage detection approach is proposed. It is based on the integration of structural damage detection using temporal moments in each time segment of measured response time history with the sensitivity analysis of the damage vector to the uncertain parameters. In both approaches, probability distribution of damage vector is estimated from those of uncertain parameters based on stochastic finite element model updating and probabilistic propagation. By comparing the two probability distribution characteristics for the undamaged and damaged models, probability of damage existence and damage extent at structural element level can be detected. Some numerical examples are used to demonstrate the performances of the two proposed approaches, respectively.

Representation of Uncertain Geometric Robot Environment Using Fuzzy Numbers

  • Kim, Wan-Joo-;Ko, Joong-Hyup;Chung, Myung-Jin
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1211-1214
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    • 1993
  • In this paper, we present a fuzzy-number-oriented methodology to model uncertain geometric robot environment and to manipulate geometric uncertainty between robot coordinate frames. We describe any geometric primitive of robot environment as a parameter vector in parameter space. Not only ill-known values of the parameterized geometric primitive but the uncertain quantities of coordinate transformation are represented by means of fuzzy numbers restricted to appropriate membership functions. For consistent interpretation about geometric primitives between different coordinate frames, we manipulate these uncertain quantities using fuzzy arithmetic.

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A New Support Vector Machines for Classifying Uncertain Data (불완전 데이터의 패턴 분석을 위한 $_{MI}$SVMs)

  • Kiyoung, Lee;Dae-Won, Kim;Doheon, Lee;Kwang H., Lee
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.10b
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    • pp.703-705
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    • 2004
  • Conventional support vector machines (SVMs) find optimal hyperplanes that have maximal margins by treating all data equivalently. In the real world, however, the data within a data set may differ in degree of uncertainty or importance due to noise, inaccuracies or missing values in the data. Hence, if all data are treated as equivalent, without considering such differences, the optimal hyperplanes identified are likely to be less optimal. In this paper, to more accurately identify the optimal hyperplane in a given uncertain data set, we propose a membership-induced distance from a hyperplane using membership values, and formulate three kinds of membership-induced SVMs.

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Robust stabilization of nonlinear uncertain systems without matching conditions (정합조건을 만족하지 않는 불확정 비선형 시스템의 강인 안정화)

  • 주진만;최윤호;박진배
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.159-162
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    • 1997
  • This paper describes robust stabilization of nonlinear single-input uncertain systems without matching conditions. We consider nonlinear systems with a vector of unknown constant parameters perturbed about a known value. The approach utilizes the generalized controller canonical form to lump the unmatched uncertainties recursively into the matched ones. This can be achieved via nonlinear coordinate transformations which depend not only on the states of the nonlinear system but also on the control input. Then the dynamic robust control law is derived and the stability result is also presented.

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Sequential Fault Detection and Isolation for Redundant Inertial Sensor Systems with Uncertain Factors

  • Kim, Jeong-Yong;Yang, Cheol-Kwan;Shim, Duk-Sun
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.2594-2599
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    • 2003
  • We consider some problems of the Modified SPRT(Sequential Probability Ratio Test) method for fault detection and isolation of inertial redundant sensor systems and propose an Advanced SPRT method to solve the problems of the Modified SPRT method. One problem of the Modified SPRT method to apply to inertial sensor system comes from the effect of inertial sensor errors such as misalignment, scale factor error and sensor bias in the parity vector, which make the Modified SPRT method hard to be applicable. The other problem is due to the correlation of parity vector components which may induce false alarm. We use a two-stage Kalman filter to remove effects of the inertial sensor errors and propose the modified parity vector and the controlled parity vector which removes the effect of correlation of parity vector components. The Advanced SPRT method is derived form the modified parity vector and the controlled parity vector. Some simulation results are presented to show the usefulness of the Advanced SPRT method to redundant inertial sensor systems.

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Dynamic Obstacle Avoidance of a Mobile Robot Using a Collision Vector (충돌 벡터를 이용한 이동로봇의 동적 장애물 회피)

  • Seo, Dae-Geun;Lyu, Eun-Tae;Lee, Jang-Myung
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.7
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    • pp.631-636
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    • 2007
  • An efficient obstacle avoidance algorithm is proposed in this paper to avoid dynamic obstacles using a collision vector while a tele-operated mobile robot is moving. For the verification of the algorithm, an operator watches through a monitor and controls the mobile robot with a force-reflection joystick. The force-reflection joystick transmits a virtual force to the operator through the Inter-net, which is generated by an adaptive impedance algorithm. To keep the mobile robot safe from collisions in an uncertain environment, the adaptive impedance algorithm generates the virtual force which changes the command of the operator by pushing the operator's hand to a direction to avoid the obstacle. In the conventional virtual force algorithm, the avoidance of moving obstacles was not solved since the operator cannot recognize the environment realistically by the limited communication bandwidth and the narrow view-angle of the camera. To achieve the dynamic obstacle avoidance, the adaptive virtual force algorithm is proposed based on the collision vector that is a normal vector from the obstacle to the mobile robot. To verify the effectiveness of the proposed algorithm, mobile robot navigation experiments with multiple moving obstacles have been performed, and the results are demonstrated.

Active assembly Method Using a Two-Arm Robot System in Highly Uncertain Environment (불확실한 환경에서 두 팔 로봇을 이용한 능동적 조립 방법)

  • 정성엽;강경대;이두용
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.73-73
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    • 2000
  • Assembly is usually performed by one robot and fixtures. This type of assembly system has Low flexibility in terms of variety of parts and part-presentation that the system can handle. This paper addresses assembly without fixtures using two-manipulator robot. An active method using force feedback is proposed for the peg-in-hole assembly in highly uncertain environment. Assembly states are described by extended contact relations. Qualitative templates for events are easily derived from the token vector of the Petrinet model. The states are recognized through identification of the events using two 6-d.o.f force/moment sensors. The proposed method is verified and evaluated through experiments with round peg- in-hole assembly.

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