• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.254-259
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• 2008

Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts; context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Networks for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.12
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• pp.1898-1902
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• 2012

In this paper, we consider the delay-dependent robust stability condition for polytopic uncertain systems with interval time-varying delay using various combinations of quantization and overflow nonlinearities. A robust stability condition for uncertain systems with time-varying delay and quantization/overflow nonlinearities is proposed by LMI(linear matrix inequality) and Lyapunov technique. It is shown that the proposed method is less conservative compared to the recent results by numerical examples.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.6
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• pp.786-796
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• 2014

This paper presents a new approach to design a robust tracking controller for linear time-invariant systems with uncertain time-delay. By introducing the model following control (MFC) structure which consists of two loops in nature, we show that the controller is capable of having a predictive control action and effectively tracking the reference output with a desired transient response as well. Three design techniques to achieve good tracking performance are suggested. It is also analytically shown that the tracking performance of the proposed scheme is more robust than that of typical single-loop feedback structure. An illustrative example is given to compare the tracking performances of the proposed methods with a single loop method.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2630-2632
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• 2000

In this paper, a control technique of Takagi-Sugeno (TS) fuzzy systems with parametric uncertainties is developed. The uncertain TS fuzzy system is represented as an uncertain multiple linear system. The control problem of TS fuzzy system is converted into the stabilization problem of a uncertain multiple linear system. A sufficient condition for robust stabilization is obtained in terms of linear matrix inequalities (LMI). A Design example is illustrated to show the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.185-189
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• 1998

This paper addresses analysis and design of a fuzzy model-based-controller for the control of uncertain SISO nonlinear systems. In the design procedure, we represent the nonlinear system by using a Takagi-Sugeno fuzzy model and construct a global fuzzy logic controller via parallel distributed compensation and sliding mode control. Unlike other parallel distributed controllers, this globally stable fuzzy controller is designed without finding a common positive definite matrix for a set of Lyapunov equations, and has good tracking performance. The stability analysis is conducted not for the fuzzy model but for the real underlying nonlinear system. Furthermore, the proposed method can be applied to partially known uncertain nonlinear systems. A numerical simulation is performed for the control of an inverted pendulum, to show the effectiveness and feasibility of the proposed fuzzy control method.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.8
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• pp.616-622
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• 2003

This paper deals with the problem of estimating the asymptotic stability region(ASR) of uncertain variable structure systems with bounded controllers. Using linear matrix inequalities(LMIs) we estimate the ASR and show the exponential stability of the closed-loop control system in the estimated ASR. We give a simple LMI-based algorithm to get estimates of the ASR. We also give a synthesis algorithm to design a switching surface which will make the estimated ASR big. Finally, we give numerical examples in order to show that our method can give better results than the previous ones for a certain class of uncertain variable structure systems with bounded controllers.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.144-149
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• 2006

This paper deals with a balanced model reduction for uncertain nonlinear systems via T-S fuzzy approach. We define a generalized controllability/observability gramian and obtain a balanced state space model using generalized gramians which can be obtained from solutions of linear matrix inequalities. We present a balanced model reduction scheme by truncating not only state variables but also uncertain elements. An upper bound of the model reduction error will also be suggested. In order to demonstrate the efficacy of our method, a numerical example will be presented.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.270-277
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• 1999

This paper deals with the maneuver detection and target tracking problem in uncertain parameter systems using a robust{{{{ { H}_{ } }}}} FIR filter to improve the unacceptable tracking performance due to the parametr uncertainty. The tracking filter used in the current paper is based on the robust{{{{ { H}_{ } }}}} FIR filter proposed by Kwon et al. [1,2] to estimate the state signal in uncertain systems with parameter uncertainty, and the basic scheme of the proposed method is the input estimation approach. Tracking performance of the maneuver detection and target tracking method proposed is compared with other techniques, Bogler allgorithm [4] and FIR tracking filter [2], via some simulations to examplify the good tracking performance of the proposed method over other techniques.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.988-991
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• 2010

This paper presents a control design for networked control systems (NCS) with uncertain time delay using model matching. The dynamics of the time delay are approximated through the Pade linearization and the uncertain delay term is recursively estimated by the recursive least square (LS) algorithm. Computer simulation illustrates that the proposed control compares favorably with a recently published control approach.

• Nuclear Engineering and Technology
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• v.35 no.4
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• pp.286-298
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• 2003

A steam explosion module, STX, has been developed using the mechanistic steam explosion analysis code, TEXAS-V, in order to estimate the dynamic load with steam explosion by implementing the module to the integrated safety analysis code, MELCOR. One of the difficulties in using mechanistic steam explosion codes is that they do not have any obvious criteria for defining some uncertain parameters such as triggering timing, triggering magnitude, mesh axial length and mesh cross-sectional area. These parameters have been user decision parts in the past. Steam explosion sample calculations and sensitivity studies on uncertain parameters were conducted to investigate those uncertain parameters. The TEXAS-V simulations were summarized in the format of a look-up table and a linear interpolation technique was adopted to calculate the steam explosion load between the data points in the table. The STX-module merged with MELCOR showed the same results as the original MELCOR and additionally it could estimate the steam explosion load in the reactor cavity.