• Title/Summary/Keyword: robust

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Robust Control of Input Delayed Systems with Structured Uncertainty (구조화된 불확실성을 갖는 입력지연 시스템의 강인제어)

  • 이보형
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.270-270
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    • 2000
  • Input delay is frequently encountered in the practical systems since measurement delay and computational delay can be represented by input delay. In this viewpoint, this paper deals with the robust control problem of input delayed systems with structured uncertainty. Robust stability conditions are provided in terms of linear matrix inequalities(LMIs) and it is shown that the proposed conditions can give less conservative maximum bound of input delay guaranteeing robust stability.

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A Method of Determining the Scale Parameter for Robust Supervised Multilayer Perceptrons

  • Park, Ro-Jin
    • Communications for Statistical Applications and Methods
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    • v.14 no.3
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    • pp.601-608
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    • 2007
  • Lee, et al. (1999) proposed a unique but universal robust objective function replacing the square objective function for the radial basis function network, and demonstrated some advantages. In this article, the robust objective function in Lee, et al. (1999) is adapted for a multilayer perceptron (MLP). The shape of the robust objective function is formed by the scale parameter. Another method of determining a proper value of that parameter is proposed.

Simultaneous Optimization Using Loss Functions in Multiple Response Robust Designs

  • Kwon, Yong Man
    • Journal of Integrative Natural Science
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    • v.14 no.3
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    • pp.73-77
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    • 2021
  • Robust design is an approach to reduce the performance variation of mutiple responses in products and processes. In fact, in many experimental designs require the simultaneous optimization of multiple responses. In this paper, we propose how to simultaneously optimize multiple responses for robust design when data are collected from a combined array. The proposed method is based on the quadratic loss function. An example is illustrated to show the proposed method.

Adaptive robust control for a direct drive SCARA robot manipulator (직접구동 SCARA 로봇 머니퓰레이터에 대한 적응견실제어)

  • Lee, Ji-Hyung;Kang, Chul-Goo
    • Journal of the Korean Society for Precision Engineering
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    • v.12 no.8
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    • pp.140-146
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    • 1995
  • In case the uncertainty existing in a system is assumed to satisfy the matching condition and to be come-bounded. Y. H. Chen proposed an adaptive robust control algorithm which introduced adaptive sheme for a design parameter into robust deterministic controls. In this paper, the adaptive robust control algorithm is applied to the position tracking control of direct drive robots, and simulation and experimental studies are conducted to evaluate control performance.

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Robust Designs to Outliers for Response Surface Experiments

  • Jeong B. Yoo;Park, Sung H.
    • Journal of the Korean Statistical Society
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    • v.20 no.2
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    • pp.147-155
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    • 1991
  • This paper treats a robust design criterion which minimizes the effects of outliers and model inadequacy, and investigates robust designs for some response surface designs. In order to develop a robust design criterion and robust design, the integrated mean squared error of *(equation omitted) over a region is utilized, where *(equation omitted). is the estimated response by the minimum bias estimation proposed by carson, Manson and Hader (1969) . According to the number of aberrant observations and their positions, the proposed criterion and designs are studied. Also further development of the proposed criterion is treated when outliers can occur in any position of a design.

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A Study on Linear Matrix Inequalities Robust Active Suspension Control System Design Algorithm

  • Park, Jung-Hyen
    • Journal of information and communication convergence engineering
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    • v.6 no.1
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    • pp.105-109
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    • 2008
  • A robust optimal control system design algorithm in active suspension equipment adopting linear matrix inequalities control system design theory is presented. The validity of the linear matrix inequalities robust control system design in active suspension system through the numerical examples is also investigated.

A survey on the robust controller (Robust 제어기에 관한 연구동향)

  • 권욱현;김상우
    • 제어로봇시스템학회:학술대회논문집
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    • 1986.10a
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    • pp.346-351
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    • 1986
  • 본 논문에서는 과거 10여년 동안의 Robust제어기에 관한 연구동향을 조사 요약하였다. Robust제어기에 관한 연구는 제어시스템의 Robustness 분석과 Robust한 제어기 설계방법으로 나뉘며 Robustness 분석은 불확실성이 구조를 갖는 경우와 구조가 없는 경우로 나뉘어 연구된다. Robust한 제어기 설계 방법에는 LQG/LTR방법과 제어기 매개변수화등이 있다. 본 논문에서는 각 방법들을 간략히 소개하고 이들을 비교하였다.

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ROBUST BOUNDARY CONTROL OF CHEMOTAXIS REACTION DIFFUSION SYSTEM

  • Ryu, Sang-Uk;Kang, Yong Han
    • Korean Journal of Mathematics
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    • v.16 no.4
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    • pp.457-470
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    • 2008
  • This paper is concerned with the robust boundary control of the chemotaxis reaction diffusion system. That is, we show that the existence of the saddle point for the robust control problem when the control and the disturbance are given by the boundary condition.

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Robust Optimization of a Resonant-type Micro-probe Using Gradient Index Based Robust Optimal Design Method (구배 지수에 근거한 강건 최적 설계 기법을 이용한 공진형 미소탐침의 강건 최적화)

  • Han, Jeong-Sam;Kwak, Byung-Man
    • Proceedings of the KSME Conference
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    • 2003.04a
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    • pp.1254-1261
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    • 2003
  • In this paper we present a simple and efficient robust optimal design formulation and its application to a resonant-type micro probe. The basic idea is to use the Gradient Index (GI) to improve robustness of the objective and constraint functions. In the robust optimal design procedure, a deterministic optimization for performance of MEMS structures is followed by design sensitivity analysis with respect to uncertainties such as fabrication errors and change of operating conditions. During the process of deterministic optimization and sensitivity analysis, dominant performance and uncertain variables are identified to define GI. The GI is incorporated as a term of objective and constraint functions in the robust optimal design formulation to make both performance and robustness improved. While most previous approaches for robust optimal design require statistical information on design variations, the proposed GI based method needs no such information and therefore is cost-efficient and easily applicable to early design stages. For the micro probe example, robust optimums are obtained to satisfy the targets for the measurement sensitivity and they are compared in terms of robustness and production yield with the deterministic optimums through the Monte Carlo simulation.

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