• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.328-330
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• 1993

In this paper, we present a robust $H^{\infty}$ controller for a state delayed system with uncertainties. The unstructured and norm bounded uncertainties enter into both the state and the input matrix, where the matching condition of the uncertainties is not assumed. A robust stabilization condition and also a robust $H^{\infty}$ stabilization condition are suggested. The robust $H^{\infty}$ controller is obtained by solving a Riccati equation which is derived from the suggested robust $H^{\infty}$ stabilization condition.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1955-1957
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• 2001

This paper propose the design method of robust tracking controller for nonlinear TS fuzzy system with uncertainties. The robust tracking controller design is presented by constraint of robust stability for nonlinear system. A sufficient condition of the robust stability is presented by LMI(Linear Matrix Inequality) soltuion in the sense of Lyapunov for TS fuzzy system with uncertainties. The effectiveness of the proposed robust tracking con design is demonstrated through a numerical simulatio.

• Proceedings of the KIPE Conference
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• 2010.11a
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• pp.298-299
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• 2010

In this paper a robust voltage controller of single-phase inverter for UPS is presented. The voltage controller is designed using ${\mu}-based$ robust control scheme to simultaneously guarantee robust stability and robust tracking performance in presence of filter and load parameter variations. Firstly the robust performance of the resulting controller is theoretically confirmed via ${\mu}-analysis$. Then simulation results for single-phase inverter system with linear and nonlinear loads demonstrate feasibility of the proposed control method providing improved performance - good regulation and fast dynamic response.

• Bulletin of the Korean Mathematical Society
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• v.56 no.6
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• pp.1467-1483
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• 2019

This paper analyzes a robust optimal reinsurance and investment strategy for an Ambiguity-Averse Insurer (AAI), who worries about model misspecification and insists on seeking robust optimal strategies. The AAI's surplus process is assumed to follow a jump-diffusion model, and he is allowed to purchase proportional reinsurance or acquire new business, meanwhile invest his surplus in a risk-free asset and a risky-asset, whose price is described by an Ornstein-Uhlenbeck process. Under the criterion for maximizing the expected exponential utility of terminal wealth, robust optimal strategy and value function are derived by applying the stochastic dynamic programming approach. Serval numerical examples are given to illustrate the impact of model parameters on the robust optimal strategies and the loss utility function from ignoring the model uncertainty.

• International Journal of Reliability and Applications
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• v.5 no.2
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• pp.59-74
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• 2004

There are many uncertain parameters associated with vibration components. Their physical parameters, the machining quality of vibration components, and the applied load acting on them are all uncertain. As a result, the natural frequency and the fatigue limits are also uncertain variables. In this paper, we express these parameters of vibration components and the frequency zone of resonance through interval models; this way, the robust reliability of the vibration components is defined. The robust reliability model measures and assesses the reliability of vibration components. The robust reliability of a cantilever beam is evaluated as an example. The results show that this method is reasonable for robust reliability analysis of vibration components because it does not require a large amount of failure data, it avoids the evaluation of the probability density function, and the computation is simple.

• Journal of the Korean Mathematical Society
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• v.56 no.3
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• pp.689-701
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• 2019

We study the recovery results of ${\ell}_p$-constrained compressive sensing (CS) with $p{\geq}1$ via robust width property and determine conditions on the number of measurements for standard Gaussian matrices under which the property holds with high probability. Our paper extends the existing results in Cahill and Mixon from ${\ell}_2$-constrained CS to ${\ell}_p$-constrained case with $p{\geq}1$ and complements the recovery analysis for robust CS with ${\ell}_p$ loss function.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4684-4705
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• 2019

Collaborative filtering recommender systems are vulnerable to shilling attacks in which malicious users may inject biased profiles to promote or demote a particular item being recommended. To tackle this problem, many robust collaborative recommendation methods have been presented. Unfortunately, the robustness of most methods is improved at the expense of prediction accuracy. In this paper, we construct a robust Bayesian probabilistic matrix factorization model for collaborative filtering recommender systems by incorporating the detection of user anomaly rating behaviors. We first detect the anomaly rating behaviors of users by the modified K-means algorithm and target item identification method to generate an indicator matrix of attack users. Then we incorporate the indicator matrix of attack users to construct a robust Bayesian probabilistic matrix factorization model and based on which a robust collaborative recommendation algorithm is devised. The experimental results on the MovieLens and Netflix datasets show that our model can significantly improve the robustness and recommendation accuracy compared with three baseline methods.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.4
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• pp.66-72
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• 2021

Since the behavior of an autonomous underwater vehicle (AUV) is influenced by disturbances and moments that are not accurately known, the depth control law of AUVs must have the ability to track the input signal and to reject disturbances simultaneously. Here, we proposed robust tracking control for controlling the depth of an AUV. An augmented closed-loop system is represented by an error dynamic equation, and we can easily show the asymptotic stability of the overall system by using a Lyapunov function. The robust tracking controller is consisted of the internal model of the command signal and a state feedback controller, and it has the ability to track the input signal and reject disturbances. The closed-loop control system is robust to parameter uncertainties. Simulation results showed the control performance of the robust tracking controller to be better than that of a P + PD controller.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.10
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• pp.157-165
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• 1995

The new formulation of designing the two degree of freedom(TDF) robust controller is proposed using $H_{\infty}$optimization and model matching method. In this formulation the feedback controller and feedforward controller are designed in a single step using $H_{\infty}$optimization procedure. Roughly speaking, the feedback controller is designed to meet robust stability and disturbance rejection specifications, while the feedforward controller is used to improve the robust model matching properties of the closed loop system. The proposed formulation will be illustrated and evaluated on a seeker scan-loop. And the performances of TDF robust controller are compared with those of the $H_{\infty}$ controller designed using Loop Shaping Design Procedure proposed by McFarlane and Glover.lover.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.275-280
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• 1986

본 연구는 LQR을 Robust하게 설계하는 방법을 다루었다. Unstructured Perturbation에 대응하기 좋으며 쉽게 다룰 수 있는 주파수 응답형 LQR criteria 선정법과, LQR의 변형으로서 Structured Perturbation에 대하여 유효한 Performance Criteria Insensitive Control을 제시하고 효과를 살펴보았다.