• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.451-456
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• 1990

We treat the problem of the robust tracking of a class of nonlinear systems which can be asymptotically decoupled in approximate sense by state variable feedback. A nonlinear control law is derived such that the tracking error in the closed loop system is uniformly bounded and tends to a certain small neighborhood of the origin. Simulation results show that simultaneous lateral and longitudinal maneuvers in airplane can be accurately performed in spite of uncertainty in stability derivatives.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.246-248
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• 2006

This paper is concerned with non-fragile guaranteed cost state feedback controller design algorithm for descriptor systems with time-varying delay and static state feedback controller with multiplicative uncertainty. The considered uncertainties are norm-bounded and time delay is time-varying. Under the condition of controller gain variations, conditions for the existence of controller satisfying asymptotic stability and non-fragility and controller design method are derived via LMI approach. Moreover, the measure of non-fragility and the upper bound to minimize guaranteed cost function are given.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.454-456
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• 1998

Traditional adaptive control algorithms are not robust to dynamic uncertainties. The adaptive control algorithms developed previously to deal with dynamic uncertainties do not facilitate quantitative design. We proposed a new robust adaptive control algorithms consists of an $H^{\infty}$ suboptimal control law and a robust parameter estimator. Numerical examples showing the effectiveness of the $H^{\infty}$ adaptive scheme are provided.

• 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.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.33-38
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• 1996

In this paper, we present a robust H\ulcorner control design method for parameter uncertain systems that have delay in both state and control input. Through a certain algebraic Riccati inequality approach, a state feedback controller is obtained. The proposed state feedback controller stabilizes parameter uncertain delay systems and guarantees disturbance attenuation within a prescribed level. An illustrative example is given to demonstrate the results of the proposed method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.10
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• pp.2651-2659
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• 2009

In this paper, inverse optimal control for nonlinear systems with structural uncertainty is considered. The first, the bounded of structural uncertainty is introduced and based on the control Lyapunov function, a theorem for the globally asymptotic stability is presented. From this a less conservative condition for the inverse optimal control is derived. The result is used to design an inverse optimal controller for a class of nonlinear systems, that improves and extends the existing results. The class of nonlinear system considered is also enlarger. The simulation results show the effectiveness of the method.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.140-147
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• 2015

In this paper, we propose a state feedback robust controller of 2-axis gimbal system which have bounded parametric uncertainty. The proposed controller is robust against dynamics variations of gimbal system and contains a dynamic compensator in order to improve a steady state error and a transient response. The stability of the closed-loop system is proved by Lyapunov approach. The performance of the proposed method is demonstrated by simulation on a 2-axis gimbal system.

• Journal of Environmental Policy
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• v.8 no.3
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• pp.163-180
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• 2009

This study attempts to investigate the preference uncertainty of respondents involved in stating their Willingness to Pay (WTP). For the Contingent Valuation Method (CVM) survey, we employed two approaches using two split samples. The respondents of one sample were given the opportunity to express intensity of preference through Multi-bounded Discrete Choice (MBDC) WTP questions, while those in the other sample were given Dichotomous Choice (DC) WTP questions. By incorporating the two elicited degrees of preference uncertainty into examining the WTP responses, we compared the two approaches. In comparing the DC model with the MBDC model, the mean WTP for the DC model was similar to PRYES in the MBDC Model. We concluded that the MBDC model estimates the various mean WTP while considering the preference uncertainty.

• Computers and Concrete
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• v.23 no.6
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• pp.433-444
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• 2019

As rice husk ash (RHA) is not produced in controlled manufacturing process like cement, its properties vary significantly even within the same lot. In fact, properties of Rice Husk Ash Based Concrete (RHABC) are largely dictated by uncertainty leading to huge deviations from their expected values. This paper proposes a Robust Cost Optimization (RCO) procedure for RHABC, which minimizes such unwanted deviation due to uncertainty and provides guarantee of achieving desired strength and workability with least possible cost. The RCO simultaneously minimizes cost of RHABC production and its deviation considering feasibility of attaining desired strength and workability in presence of uncertainty. RHA related properties have been modeled as uncertain-but-bounded type as associated probability density function is not available. Metamodeling technique is adopted in this work for generating explicit expressions of constraint functions required for formulation of RCO. In doing so, the Moving Least Squares Method is explored in place of conventional Least Square Method (LSM) to ensure accuracy of the RCO. The efficiency by the proposed MLSM based RCO is validated by experimental studies. The error by the LSM and accuracy by the MLSM predictions are clearly envisaged from the test results. The experimental results show good agreement with the proposed MLSM based RCO predicted mix properties. The present RCO procedure yields RHABC mixes which is almost insensitive to uncertainty (i.e., robust solution) with nominal deviation from experimental mean values. At the same time, desired reliability of satisfying the constraints is achieved with marginal increment in cost.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.5
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• pp.26-33
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• 2002

The design method of robust $H_{\infty}$ filtering for discrete-time uncertain linear systems is investigated in this paper. The uncertain parameters are assumed to be unknown but belonging to known convex compact set of polytope type. The objective is to design a stable robust $H_{\infty}$ filter guaranteeing the asymptotic stability of filtering error dynamics and present an $L_2$ induced norm bound analytically for the modified $H_{\infty}$ performance measure. The sufficient condition for the existence of robust $H_{\infty}$ filter and the filter design method are established by LMI(linear matrix inequality) approach, which can be solved efficiently by convex optimization. The proposed algorithm is checked through an example.