• Title, Summary, Keyword: Robust

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Suboptimal Robust Generalized H2 Filtering using Linear Matrix Inequalities

  • Ra, Won-Sang;Jin, Seung-Hee;Yoon, Tae-Sung;Park, Jin-Bae
    • Transactions on Control, Automation and Systems Engineering
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    • v.1 no.2
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    • pp.134-140
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    • 1999
  • The robust generalized H2 filtering problem for a class of discrete time uncertain linear systems satisfying the sum quadratic constraints(SQCs) is considered. The objective of this paper is to develop robust stability condition using SQCs and design a robust generalized Ha filter to take place of the existing robust Kalman filter. The robust generalized H2 filter is designed based on newly derived robust stability condition. The robust generalized Ha filter bounds the energy to peak gain from the energy bounded exogenous disturbances to the estimation errors under the given positive scalar ${\gamma}$. Unlike the robust Lalman filter, it does not require any spectral assumptions about the exogenous disturbances . Therefore the robust generalized H2 filter can be considered as a deterministic formulation of the robust Kalman filter. Moreover, the variance of the estimation error obtained by the proposed filter is lower than that by the existing robust Kalman filter. The robustness of the robust generalized H2 filter against the uncertainty and the exogenous signal is illustrated by a simple numerical example.

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A Robust Disturbance Observer for Uncertain Linear Systmes (불확실한 성형시스템에 대한 강인 외란관측기)

  • Kim, Jun-Sik;O, Jun-Ho
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.20 no.9
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    • pp.2731-2743
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    • 1996
  • When modeling error is large of plant is time-varying, it is hard to obtain good robust performance and robust stability by conventional contorl methods. Here, we need to design a robust controller bearing modeling error. In this paper, based on recently developed Time Delay Control(TDC) and Disturbance Observer the output feedback Robust Disturbance Observer(RDO), which is easily combined with general linear control, is proposed. Proposed RDO is derived from extending the main idea of Disturbance Observer to multi-input multi-output linear system. RDO solves robust stability problem of Disturbance Observer and has the robust performance same as nominal performance. RDO controlled dual stage positioning system shows excellent robust performance.

Robust Cross Validation Score

  • Park, Dong-Ryeon
    • Communications for Statistical Applications and Methods
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    • v.12 no.2
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    • pp.413-423
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    • 2005
  • Consider the problem of estimating the underlying regression function from a set of noisy data which is contaminated by a long tailed error distribution. There exist several robust smoothing techniques and these are turned out to be very useful to reduce the influence of outlying observations. However, no matter what kind of robust smoother we use, we should choose the smoothing parameter and relatively less attention has been made for the robust bandwidth selection method. In this paper, we adopt the idea of robust location parameter estimation technique and propose the robust cross validation score functions.

ROBUST DUALITY FOR GENERALIZED INVEX PROGRAMMING PROBLEMS

  • Kim, Moon Hee
    • Communications of the Korean Mathematical Society
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    • v.28 no.2
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    • pp.419-423
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    • 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.

System Modeling and Robust Control of an AMB Spindle : Part II A Robust Controller Design and its Implementation

  • Ahn, Hyeong-Joon;Han, Dong-Chul
    • Journal of Mechanical Science and Technology
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    • v.17 no.12
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    • pp.1855-1866
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    • 2003
  • This paper discusses an entire procedure for a robust controller design and its implementation of an AMB (active magnetic bearing) spindle, which is part II of the papers presenting details of system modeling and robust control of an AMB spindle. Since there are various uncertainties in an AMB system and reliability is the most important factor for applications, robust control naturally gains attentions in this field. However, tight evaluations of various uncertainties based on experimental data and appropriate performance weightings for an AMB spindle are still ongoing research topics. In addition, there are few publications on experimental justification of a designed robust controller. In this paper, uncertainties for the AMB spindle are classified and described based on the measurement and identification results of part I, and an appropriate performance weighting scheme for the AMB spindle is developed. Then, a robust control is designed through the mixed ${\mu}$ synthesis based on the validated accurate nominal model of part I, and the robust controller is reduced considering its closed loop performance. The reduced robust controller is implemented and confirmed with measurements of closed-loop responses. The AMB spindle is operated up to 57,600 rpm and performance of the designed controller is compared with a benchmark PID controller through experiments. Experiments show that the robust controller offers higher stiffness and more efficient control of rigid modes than the benchmark PID controller.

Robust $H^{\infty}$ Performance Controller Design with Parameter Uncertainty and Unmodeled Dynamics (파라미터 불확실성 및 모델 불확실성에 대한 $H^{\infty}$ 견실성능 제어기 설계)

  • Lee, Kap-Rai;Oh, Do-Chang;Park, Hong-Bae
    • Journal of Institute of Control, Robotics and Systems
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    • v.3 no.1
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    • pp.9-16
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    • 1997
  • The method of designing robust two degree of freedom(2 DOF) controllers for linear systems with parameter uncertainties and unmodeled dynamics is presented in this paper. Robust performance condition that accounts for robust model matching of closed loop system and disturbance rejection is derived. Using the robust performance condition, the feedback controller is designed to meet robust stability and disturbance rejection specifications, while prefilter is used to improve the robust model matching properties. The $H^{\infty}$ and $\mu$ controller for six degree of freedom vehicle with parameter variations are designed and compared. Simulations for hydrodynamic parameter variations and disturbance are presented to demonstrate the achievement of good robust performance.

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A tuning method for robust PID controller (강인 PID 제어기 설계)

  • 윤상준;이상정
    • 제어로봇시스템학회:학술대회논문집
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    • pp.585-588
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    • 1996
  • The conventional output feedback robust control designs are very useful for systems under parameter perturbation and uncertain disturbance. However these designs are very complicated and not easily implemented for industrial applications. So, this paper proposes a robust PID controller design method via genetic searching algorithm.

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OPTIMALITY CONDITIONS AND DUALITY IN NONDIFFERENTIABLE ROBUST OPTIMIZATION PROBLEMS

  • Kim, Moon Hee
    • East Asian mathematical journal
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    • v.31 no.3
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    • pp.371-377
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    • 2015
  • We consider a nondifferentiable robust optimization problem, which has a maximum function of continuously differentiable functions and support functions as its objective function, continuously differentiable functions as its constraint functions. We prove optimality conditions for the nondifferentiable robust optimization problem. We formulate a Wolfe type dual problem for the nondifferentiable robust optimization problem and prove duality theorems.

Self-tuning Robust Regression Estimation

  • Park, You-Sung;Lee, Dong-Hee
    • Proceedings of the Korean Statistical Society Conference
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    • pp.257-262
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    • 2003
  • We introduce a new robust regression estimator, self-tuning regression estimator. Various robust estimators have been developed with discovery for theories and applications since Huber introduced M-estimator at 1960's. We start by announcing various robust estimators and their properties, including their advantages and disadvantages, and furthermore, new estimator overcomes drawbacks of other robust regression estimators, such as ineffective computation on preserving robustness properties.

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