• 제목/요약/키워드: Lyapunov-based analysis

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뇌파신호의 카오스 특징 추출을 위한 통합 시스템의 개발 (A Study on the Development of Integrated Chaos Analysis System for EEG)

  • 우용호;김현술;김택수;최윤호;박상희
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1995년도 하계학술대회 논문집 B
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    • pp.962-964
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    • 1995
  • In this paper, an integrated chaos analysis system for EEG (ICASE) is designed for the analysis of brain functions based on the chaos theory. Nonlinear dynamic characteristics of EEG such as 3-D attractor, Poincare section, correlation dimension, Lyapunov exponents and power spectrum are extracted by this system. The results show that chaotic attractors which indicate the presence of deterministic, dynamics of complex nature could be identified from a routine EEG recording for normal and pathological activity. This proves that the chaotic analysis of EEG may be an appropriate tool in the classification of brain activity and thus a possible diagnostic tool.

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Observer Based Nonlinear State Feedback Control of PEM Fuel Cell Systems

  • Kim, Eung-Seok
    • Journal of Electrical Engineering and Technology
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    • 제7권6호
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    • pp.891-897
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    • 2012
  • In this paper, the observer based nonlinear state feedback controller has been developed to control the pressures of the oxygen and the hydrogen in the PEM(Proton Exchange Membrane) fuel cell system. Nonlinear model of the PEM fuel cell system was introduced to study the design problems of the state observer and model based controller. A cascade observer using the filtering technique was used to estimate the pressure derivatives of the cathode and the anode in the system. In order to estimate the pressures of the cathode and the anode, the sliding mode observer was designed by using these pressure derivatives. To estimate the oxygen pressure and the hydrogen pressure in the system, the nonlinear state observer was designed by using the cathode pressure estimates and the anode it. These results will be very useful to design the state feedback controller. The validity of the proposed observers and the controller has been investigated by using the Lyapunov's stability analysis strategy.

시스템 에어컨의 온도 제어를 위한 부하 예측 기반 스위칭 모델 예측 제어 (Heat Load Estimation-Based Switching Explicit Model Predictive Temperature Control for VRF Systems)

  • 김준영;이상문
    • 대한임베디드공학회논문지
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    • 제19권3호
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    • pp.123-130
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    • 2024
  • This paper proposes an EMPC (Explicit Model Predictive Controller) for temperature tracking control based on heat load prediction by an ESO (Extended State Observer) for a variable cooling circulation system with multiple indoor units connected to one outdoor unit. In this system, heat transfer and heat loss relative to the input temperature are modeled using system dynamics. Using this model, we design an EMPC based on an ESO that is robust to temperature changes and depends on airflow. To determine the stability of both the controller and the observer, asymptotic stability is verified through Lyapunov stability analysis. Finally, to validate the performance of the proposed controller, simulations are conducted under three scenarios with varying airflow, set temperature, and heat load.

뉴럴네트워크를 이용한 산업용 로봇의 동특성 해석 (Dynamics Analysis of Industrial Robot Using Neural Network)

  • 이진
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 1997년도 춘계학술대회 논문집
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    • pp.62-67
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    • 1997
  • This paper reprdsents a new scheme of neural network control system analysis the robustues of robot manipulator using digital signal processors. Digtal signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In additions, DSPs are a s fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. Durng past decade it was proposed the well-established theorys for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. The proposed neuro network control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method.

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엔드밀가공시 복합계측 신호를 이용한 공구 마멸의 카오스적 해석 (Chaotic analysis of tool wear using multi-sensor signal in end-milling process)

  • Kim, J.S.;Kang, M.C.;Ku, S.J.
    • 한국정밀공학회지
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    • 제14권11호
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    • pp.93-101
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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 control 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 milling process. Then, it will be verified that cutting force is low-dimensional chaos by calculating Lyapunov exponents. Fractal dimension, embedding dimension. And it will be investigated that the relation between characteristic parameter calculated from sensor signal and tool wear.

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비선형(非線型) 시스템의 퍼지 모델링 기법과 안정도(安定度) 해석(解析)에 관한 연구 (Fuzzy Modeling Technique of Nonlinear Dynamical System and Its Stability Analysis)

  • 이준탁;소명옥;이상석;지석준;김태우
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1995년도 하계학술대회 논문집 B
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    • pp.801-803
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    • 1995
  • This paper presents the linearized fuzzy modeling technique of nonlinear dynamical system and the stability analysis of fuzzy control system. Firstly, the nonlinear system is partitionized by multiple linear fuzzy subcontrol systems based on fuzzy linguistic variables and fuzzy rules. Secondly, the disturbance adaptation controllers which guarrantee the global asymptotic stability of each fuzzy subsystem by an optimal feedback control law are designed and the stability analysis procedures of the total fuzzy control system using Lyapunov functions and eigenvalues are discussed in detail through a given illustrative example.

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뉴트럴 타입 시간 지연을 갖는 네트워크 기반 시스템의 샘플치 퍼지 제어기 설계 (Sampled-data Fuzzy Controller for Network-based Systems with Neutral Type Delays)

  • 주영훈
    • 한국지능시스템학회논문지
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    • 제18권2호
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    • pp.151-156
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    • 2008
  • 본 논문은 뉴트럴 타입 시간 지연을 가지는 네트워크 기반 시스템의 안정도 분석 및 샘플치 퍼지 제어기 설계 방법에 관하여 논의한다. 먼저 대상이 되는 비선형 네트워크 시스템을 T-S (Takagi-Sugeno) 퍼지 모델로 표현한다. 제안하는 샘플치 퍼지 제어기를 모델링하는 퍼지 규칙과 같은 멤버쉽 함수를 가지게 설계한다. Lyapunov-Krasovskii의 안정화 이론을 도입하여 이를 바탕으로 뉴트럴 형태의 시간 지연을 갖는 T-S 퍼지 시스템의 안정도를 판별한다. T-S 퍼지 시스템의 안정도 조건을 제시하고 선형 행렬 부등식의 형태로 표현한다. 제안된 선형 행렬 부등식의 해를 통하여 샘플치 퍼지 제어기의 이득 값을 설계한다. 마지막으로, 본 논문에서 제안한 방법의 적용 가능성과 일반성을 평가하기 위하여 수치적인 예를 적용한다.

Stability Analysis of a Multi-Link TCP Vegas Model

  • Park, Poo-Gyeon;Choi, Doo-Jin;Choi, Yoon-Jong;Ko, Jeong-Wan
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.1072-1077
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    • 2004
  • This paper provides a new approach to analyze the stability of a general multi-link TCP Vegas, which is a kind of feedback-based congestion algorithm. Whereas the conventional approaches use the approximately linearized model of the TCP Vegas along equilibrium pints, this approach models a multi-link TCP Vegas network in the form of a piecewise linear multiple time-delay system. And then, based on the exactly characterized dynamic model, this paper presents a new stability criterion via a piecewise and multiple delay-dependent Lyapunov-Krasovskii function. Especially, the resulting stability criterion is formulated in terms of linear matrix inequalities (LMIs).

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표적 추적 성능 최적화 및 충돌 회피를 위한 다수 에이전트 분산 제어 (Decentralized Control of Multiple Agents for Optimizing Target Tracking Performance and Collision Avoidance)

  • 김영주;방효충
    • 제어로봇시스템학회논문지
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    • 제22권9호
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    • pp.693-698
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    • 2016
  • A decentralized control method is proposed to enable a group of robots to achieve maximum performance in multisensory target tracking while avoiding collision with the target. The decentralized control was designed based on navigation function formalism. The study showed that the multiple agent system converged to the positions providing the maximum performance by the decentralized controller, based on Lyapunov and Hessian theory. An exemplary simulation was given for a multiple agent system tracking a stationary target.

SRM 제어방법들에 대한 적응관측기들의 분석 (Study on the analysis Adaptive Observers to Control SRM Control Meathod)

  • 신재화
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2007년도 학술대회 논문집 전문대학교육위원
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    • pp.160-164
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    • 2007
  • MRAS observer, which is based on adaptive control theory, estimates speed and position by using optimal observer gains on the basis of Lyapunov stability theory. However, in case of MRAS theory, position estimation error is in existence because of non-linearity for inductance variation and limit cycles for position estimation. The adaptive sliding observer based on the variable structure control theory estimates the speed and position for zero of estimation error by using the sliding surface equal to the error between speed and position estimation. The binary observer estimates the rotor speed and rotor flux with alleviation of the high-frequency chattering, and retains the benefits achieved in the conventional sliding observer, such as robustness to parameter and disturbance variations. The speed and position sensorless control of SRM under the load and inductance variation is verified by the experimental results.

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