• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.172-177
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• 2006

In the networked control system (NCS), the uncertain network-induced delay and nonlinear controlled object are the main problems, because they can degrade the performance of the control system and even destabilize it. In this paper, a class of uncertain and nonlinear networked control systems is discussed and its sufficient condition for the robust asymptotic stability is presented. Further, the maximum network-induced delay that insures the system stability is obtained. The Lyapunov and LMI theorems are employed to investigate the problem. The result of an illustrative example shows that the robust stability analysis is sufficient.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.189-192
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• 2001

뇌 기능의 연구수단으로써 널리 사용되고 있는 뇌파(Electroencephalogram)는 측정시에 노이즈(noise)나 잡파(Artifacts)가 섞여서 측정되기 쉽다. 이러한 노이즈나 잡파들을 제거하기 위하여 미지의 혼합된 신호들을 분리하는데 적용되고 있는 통계적인 처리 방식인 독립성분분석(ICA) 알고리즘을 뇌파에 적용하여 그 결과를 알아보았다. 본 연구에서는 정상인의 안구운동(Eye Movement)상태의 뇌파 신호에 대해서 독립성분분석을 적용하여 안구운동과 관련된 잡파가 포함된 원래의 뇌파신호(Original EEG Signal)와 제거한 다음의 뇌파신호(Corrected EEG Signal)에 대하여 비선형 분석법을 사용하여 두 신호의 유의한 차이점을 밝히고, 분리된 독립 신호들의 해부학적 발생위치 및 분포를 추정하였다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.437-450
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• 1994

The problem of testing for a change in the parameter of a stochastic process is particularly important in simulation studies. In studies of the steady state characteristics of a simulation model, it is important to identify initialization bias and to evaluate efforts to control this problem. A simulation output have the characteristics of chaotic behavior because of sensitive dependence on initial conditions. For that reason, we will apply Lyapunov exponent for diagnosis of chaotic motion to simulation output analysis. This paper proposes two methods for diagnosis of steady state in simulation output. In order to evaluate the performance and effectiveness of these methods using chaos theory, M/M/I(.inf.) queueing model is used for testing point estimator, average bias.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2085-2086
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• 2006

This paper addresses the problem of stability analysis and control synthesis of a digital fuzzy control systems. The authors shows that the stability properties (in the Lyapunov sense) of a digital fuzzy control system can be deduced from the stability properties of the its approximate discretization in the sufficiently small sampling time.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.506-515
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• 2006

This paper studies an intelligent digital control for nonlinear systems with multirate sampling. It is worth noting that the multirate control design is addressed for a given nonlinear system represented by Takagi-Sugeno (T-S) fuzzy models. The main features of the proposed method are that i) it is provided that the sufficient conditions for stabilization of the discrete-time T-S fuzzy system in the sense of Lyapunov stability criterion, which is can be formulated in the linear matrix inequalities (LMIs); and ii) the stability properties of the trivial solution of the digital control system can be deduced from that of the solution of its discretized versions. An example is provided for showing the feasibility of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.11
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• pp.895-900
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• 2005

We derive a linear matrix inequality(LMI) condition guaranteeing that any invariant zeros of a triple (A, B, C) lie in the open left half plane of the complex plane, i.e. $C(sI-A)^{-1}B$ is minimum phase. The LMI condition is equivalent to a certain constrained Lyapunov matrix equation which can be found in many results relating to stability analysis or control design. We show that the LMI condition can be used to simplify various control engineering problems such as a dynamic output feedback control problem, a variable structure static output feedback control problem, and a nonlinear system observer design problem. Finally, we give some numerical examples.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.817-821
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• 1997

Ever since the nonlinearity of machine tool dynamics was established, researchers attempted to make use of this fact to devise better monitoring, diagnostics and system, which were hitherto based on linear models. Theory of chaos, which explains many nonlinear phenomena comes handy for furthering the analysis using nonlinear model. In this study, measuring system will be constructed using multi-sensor (Tool Dynamometer, Acoustic Emission) in end millingprocess. Then, it will be verified that cutting force is low-dimensional deterministic chaos calculating Lyapunov exponents, Fractal dimension, Embedding dimension. Aen it will be investigated that the relations between characteristic parameter caculated form sensor signal and tool wear.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.169-172
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• 1999

In this paper, piecewise quadratic Lyapunov functions are used to analyze the stability of fuzzy-model-based controller. We represent the nonlinear system using a Takagi-Sugeno fuzzy model, which represent the given nonlinear system by fuzzy inference rules and local linear dynamic models. The proposed stability analysis technique is developed by dividing the whole fuzzy system into the smaller separate fuzry systems to reduce the conservatism. Some necessary and sufficient conditions for the proposed method are obtained. Finally, stability of the closed system with various kinds of controller for TS fuzzy model is checked through the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.72-81
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• 2009

This paper presents a robust adaptive control method using model reference control strategy against autonomous robot systems with random friction nature. We approximate a nonlinear robot system model by means of a feedback linearization approach to derive nominal control law. We construct a Least Square (LS) based observer to estimate friction dynamics online and then represent a perturbed system model with respect to approximation error between an actual friction and its estimation. Model reference based control design is achieved to implement an auxiliary control in order for reducing control error in practice due to system perturbation. Additionally, we conduct theoretical study to demonstrate stability of the perturbed system model through Lyapunov theory. Numerical simulation is carried out for evaluating the proposed control methodology and demonstrating its superiority by comparing it to a traditional nominal control method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.8
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• pp.407-414
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• 2000

This paper addresses the analysis and design of fuzzy control systems for a class of complex uncertain single-input single-output nonlinear systems. The proposed method represents the nonlinear system using a Takagi-Cugeno fuzzy model and construct a global fuzzy logic controller by blending all local state feedback controllers with a sliding mode controller. Unlike the commonly used parallel distributed compensation technique, we can design a global stable fuzzy controller without finding a common Lyapunov function for all local control systems, and can obtain good tracking performance by using sliding mode control theory. Furthermore, stability analysis is carried out not for the fuzzy model but for the real nonlinear system with uncertainties. Duffing forced oscillation sysmte is used as an example to show the effectiveness and feasibility of the proposed method.