• Title/Summary/Keyword: robust analysis

Search Result 2,046, Processing Time 0.027 seconds

Robust attitude control and analysis for 3-axis stabilized spacecraft using sliding mode control (슬라이딩 모드 제어를 이용한 3축 안정화 위성의 자세 제어및 강건성 해석)

  • 신동준;김진호
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 1997.10a
    • /
    • pp.692-695
    • /
    • 1997
  • Nonlinear robust attitude controller for 3-axis stabilized spacecraft is designed. Robust stability analysis for nonlinear spacecraft system with disturbance is conducted. External disturbances and parametric uncertainties decrease Spacecraft's attitude pointing accuracy. Sliding Mode Control(SMC) provides stability of system in the face of these disturbances and uncertainties. The concept of quadratic boundedness and quadratic stability are applied to the robust analysis for the nonlinear spacecraft system subject to bounded disturbance torques. Numerical simulation is conducted to compare the analysis result and actual nonlinear simulation. The simulation show that analysis result is valid.

  • PDF

Robust Parameter Design for Multiple Quality Characteristics using Factor Analysis

  • Kwon, Yong-Man;Chang, Duk-Joon
    • 한국데이터정보과학회:학술대회논문집
    • /
    • 2004.04a
    • /
    • pp.131-139
    • /
    • 2004
  • Robust parameter design is to identify appropriate settings of control factors that make the system's performance robust to changes in the noise factors that represent the source of variation. In this paper, we introduce a factor analysis approach to simultaneously optimize multiple quality characteristics in the robust parameter design. An example is illustrated to compare it with already proposed method.

  • PDF

Robust Design for Multiple Quality Characteristics using Principal Component Analysis

  • Kwon, Yong-Man;Hong, Yeon-Woong
    • Journal of the Korean Data and Information Science Society
    • /
    • v.14 no.3
    • /
    • pp.545-551
    • /
    • 2003
  • Robust design is to identify appropriate settings of control factors that make the system's performance robust to changes in the noise factors that represent the source of variation. In this paper we propose how to simultaneously optimize multiple quality characteristics using the principal component analysis of multivariate statistical analysis. An example is illustrated to compare it with already proposed method.

  • PDF

Robust Simple Correspondence Analysis

  • Park, Yong-Seok;Huh, Myung-Hoe
    • Journal of the Korean Statistical Society
    • /
    • v.28 no.3
    • /
    • pp.337-346
    • /
    • 1999
  • Simple correspondence analysis is a technique for giving a joint display of points representing both the rows and columns of an n$\times$p two-way contigency table. In simple correspondence analysis, the singular value decomposition is the main algebraic tool. But, Choi and Huh(1996) pointed out the singular value decomposition is not robust. Instead, they developed a robust singular value decomposition and provided applications in principal component analysis and biplots. In this article, by using the analogous procedures of Choi and Huh(1996), we derive a robust version of simple correspondence analysis.

  • PDF

Robust Design of Mechanisms Using the Response Surfae Analysis (반응표면분석법을 이용한 기구의 강건설계)

  • 한형석;박태원
    • Proceedings of the Korean Society of Precision Engineering Conference
    • /
    • 1996.04a
    • /
    • pp.743-748
    • /
    • 1996
  • In this study a method for a robust design of mechanisms is proposed. The method used in the experimental anlysis and quqlity engineering is applied for mechanisms design. A mathematical model for a mechanism is estimated by the responese surface analysis and the robust design can be carried out. The method can be applied for mechanisms generally. Furthermore because the method can be used in the design stage using the computer model, improved quality and lower cost of the product is achieved even in the design stage.

  • PDF

Robust Guaranteed Performance Control of Uncertain Linear Systems (불확정성 선형 시스템의 강인 성능 보장 제어)

  • Kim, Jin-Hoon
    • The Transactions of the Korean Institute of Electrical Engineers A
    • /
    • v.48 no.5
    • /
    • pp.553-559
    • /
    • 1999
  • The robust control problem of the linear systems with uncertainty is classified as the robust stability problem guaranteeing the stability and the robust performance problem guaranteeing the disired performance. In this paper, we considered the robust performance analysis problem, which find the upper buund of the quadratic performance of the uncertain linear system, and the robust guaranteed performance controller design problem which design a controller guaranteeing the desired quadratic performance. At first, we treated the analysis problem and presented the two results; one is dependent on the performance of the nominal system and another is independent on this. And we treated the design method guaranteeing the desired performance for the uncertain linear systems, Finally, we show the usefulness of our results by numerical examples.

  • PDF

Analysis of Degradation Data Using Robust Experimental Design (강건 실험계획법을 이용한 열화자료의 분석)

  • 서순근;하천수
    • Journal of Korean Society for Quality Management
    • /
    • v.32 no.1
    • /
    • pp.113-129
    • /
    • 2004
  • The reliability of the product can be improved by making the product less sensitive to noises. Especially, it Is important to make products robust against various noise factors encountered in production and field environments. In this paper, the phenomenon of degradation assumes a simple random coefficient degradation model to present analysis procedures of degradation data for robust experimental design. To alleviate weak points of previous studies, such as Taguchi's, Wasserman's, and pseudo failure time methods, novel techniques for analysis of degradation data using the cross array that regards amount of degradation as a dynamic characteristic for time are proposed. Analysis approach for degradation data using robust experimental design are classified by assumptions on parametric or nonparametric degradation rate(or slope). Also, a simulation study demonstrates the superiority of proposed methods over some previous works.

Evaluation of limit load analysis for pressure vessels - Part II: Robust methods

  • Chen, Xiaohui;Gao, Bingjun;Wang, Xingang
    • Steel and Composite Structures
    • /
    • v.23 no.1
    • /
    • pp.131-142
    • /
    • 2017
  • Determining limit load for a pressure bearing structure using elastic-plastic finite element analysis was computationally very expensive. A series of robust methods using elastic modulus adjustment techniques (EMAP) to identify the limit load directly were proposed. The numerical implementation of the robust method had the potential to be an attractive alternative to elastic-plastic finite element analysis since it was simple, and required less computational effort and computer storage space. Another attractive feature was that the method provided a go/no go criterion for the limit load, whereas the results of an elastic-plastic analysis were often difficult to interpret near the limit load since it came from human sources. To explore the performance of the method further, it was applied to a number of configurations that include two-dimensional and three-dimensional effects. In this study, limit load of cylinder with nozzle was determined by the robust methods.

ROBUST DUALITY FOR GENERALIZED INVEX PROGRAMMING PROBLEMS

  • Kim, Moon Hee
    • Communications of the Korean Mathematical Society
    • /
    • v.28 no.2
    • /
    • pp.419-423
    • /
    • 2013
  • In this paper we present a robust duality theory for generalized convex programming problems under data uncertainty. Recently, Jeyakumar, Li and Lee [Nonlinear Analysis 75 (2012), no. 3, 1362-1373] established a robust duality theory for generalized convex programming problems in the face of data uncertainty. Furthermore, we extend results of Jeyakumar, Li and Lee for an uncertain multiobjective robust optimization problem.

A Robust Principal Component Neural Network

  • Changha Hwang;Park, Hyejung;A, Eunyoung-N
    • Communications for Statistical Applications and Methods
    • /
    • v.8 no.3
    • /
    • pp.625-632
    • /
    • 2001
  • Principal component analysis(PCA) is a multivariate technique falling under the general title of factor analysis. The purpose of PCA is to Identify the dependence structure behind a multivariate stochastic observation In order to obtain a compact description of it. In engineering field PCA is utilized mainly (or data compression and restoration. In this paper we propose a new robust Hebbian algorithm for robust PCA. This algorithm is based on a hyperbolic tangent function due to Hampel ef al.(1989) which is known to be robust in Statistics. We do two experiments to investigate the performance of the new robust Hebbian learning algorithm for robust PCA.

  • PDF