• 제목/요약/키워드: Lyapunov Method

검색결과 696건 처리시간 0.031초

Robust Control of Planar Biped Robots in Single Support Phase Using Intelligent Adaptive Backstepping Technique

  • Yoo, Sung-Jin;Park, Jin-Rae;Choi, Yoon-Ho
    • International Journal of Control, Automation, and Systems
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    • 제5권3호
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    • pp.269-282
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    • 2007
  • This paper presents a robust control method via the intelligent adaptive backstepping design technique for stable walking of nine-link biped robots with unknown model uncertainties and external disturbances. In our control structure, the self recurrent wavelet neural network(SRWNN) which has the information storage ability is used to observe the uncertainties of the biped robots. The adaptation laws for all weights of the SRWNN are induced from the Lyapunov stability theorem, which are used for on-line controlling biped robots. Also, we prove that all signals in the closed-loop adaptive system are uniformly ultimately bounded. Through computer simulations of a nine-link biped robot with model uncertainties and external disturbances, we illustrate the effectiveness of the proposed control system.

유전 알고리듬과 퍼지논리 시스템을 이용한 비선형 시스템의 피드백 선형화 제어 (Feedback linearization control of a nonlinear system using genetic algorithms and fuzzy logic system)

  • 최영길;김성현;심귀보;전홍태
    • 전자공학회논문지S
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    • 제34S권3호
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    • pp.46-54
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    • 1997
  • In this paper, we psropose the feedback linearization technique for a nonlinear system using genetic algorithms (GAs) and fuzzy logic system. The proposed control scheme approximates the nonlinear term of a nonlinear system using the fuzzy logic system and computes the control input for cancelling the nonlinear term. Then in the fuzzy logic system, the number and shape of membership function of the premise aprt will be tuned to minimize the control error boundary using GAs. And the parameters of the consequence of fuzzy rule will be tuned by the adaptive laws based on lyapunov stability theory in order to guarantee the closed loop stability of control system. The evolution of fuzzy logic system is processed during the on-line adaptive control. The effectiveness of proposed method will be demonstrated by computer simulation of simple nonlinear sytem.

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일정한 기준신호를 추적하는 MRAC시스템에 대한 파라미터 수렴특성 (Parameter convergence properties for MRAC system with a constant reference signal tracking)

  • 민병태;김성덕;양해원
    • 한국통신학회논문지
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    • 제13권1호
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    • pp.1-11
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    • 1988
  • 本 論文은 일정한 基準信號를 사용하는 基準모델 適應制御 시스템에 대한 可調節 파라미터의 有界性을 說明한다. 이 解析法은, Lyapunov函數의 또다른 性質로서 適應시스템의 安定度는 물론, 파라미터의 存在性, 有界性 및 有界領域을 밝힐 수 있다는 사실에 동기되었다. 2가지 適應則, 즉 一般的인 句配法(GGM) 및 最小自秉法(LSM)에 대하여, 여기서 提示된 새로운 方法에 의하여 파라미터 空間의 유일한 解集合을 확립할 수 있다. 파라미터 空間 解析法의 效率性을 證明하기 위한 電算機 시뮬레이션 結果도 역시 검토한다.

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적응 슬라이딩 모드 관측기를 이용한 영구자석 동기전동기의 센서리스 속도제어 (Sensorless Speed Control of PMSM using an Adaptive Sliding Mode Observer)

  • 한윤석;김영석
    • 대한전기학회논문지:전기기기및에너지변환시스템부문B
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    • 제51권2호
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    • pp.83-91
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    • 2002
  • This paper presents a new speed and position sensorless control method of permanent magnet synchronous motors based on the sliding mode observer. Since the parameter of the dynamic equation such as machine inertia or viscosity friction coefficient are not well known and these values can be easily changed generally during normal operation, there are many restrictions in the actual implementation. The proposed adaptive sliding mode observer applies adaptive scheme so that observer may overcome the problem caused by using the dynamic equation. Furthermore, using the Lyapunov Function, the adaptive sliding mode observer can estimate rotor speed as well as stator resistance. The feasibility of the Proposed observer is verified cia the experiments.

A Design of Adaptive Controller for Transportation System with Dynamic Friction

  • Lee, Jin-Woo;Seo, Jeon-Hyun;Han, Seung-Hoon;Lee, Kwon-Soon
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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    • pp.199-204
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    • 2006
  • In this paper, we propose an adaptive control algorithm to improve the position accuracy and reduce the nonlinear friction effects for linear motion servo system. Especially, the considered system includes not only the variation of the mass of the mover but also the friction change by the normal force. To adapt to these problems, we designed the controller with the mass estimator and the compensator by observing the variation of normal force. Finally, the numerical simulation results are presented in order to show the effectiveness of the proposed method to improve the position accuracy compared to other control methods.

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RBFN를 이용한 로봇 매니퓰레이터의 신경망 적응 제어 (Neuro-Adaptive Control of Robot Manipulator Using RBFN)

  • 김정대;이민중;최영규;김성신
    • 대한전기학회논문지:시스템및제어부문D
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    • 제50권1호
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    • pp.38-44
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    • 2001
  • This paper investigates the direct adaptive control of nonlinear systems using RBFN(radial basis function networks). The structure of the controller consists of a fixed PD controller and a RBFN controller in parallel. An adaptation law for the parameters of RBFN is developed based on the Lyapunov stability theory to guarantee the stability of the overall control system. The filtered tracking error between the system output and the desired output is shown to be UUB(uniformly ultimately bounded). To evaluate the performance of the controller, the proposed method is applied to the trajectory contro of the two-link manipulator.

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RBFN을 이용한 로봇 매뉴퓰레이터의 실시간 제어 (The Neuro-Adaptive Control of Robotic Manipulators using RBFN)

  • 김정대;이민중;최영규;김성신
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 하계학술대회 논문집 G
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    • pp.2992-2994
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    • 1999
  • This paper investigates the direct adaptive control of nonlinear systems using RBFN(radial basis function networks). The structure of the controller consists of a fixed PD controller and a RBFN controller in parallel. An adaptation law for the weight adjustment is developed based on the Lyapunov stability theory to guarantee the stability of the overall control scheme. Also, the tracking errors between the system outputs and the desired outputs converge to zero asymptotically. To evaluate the performance of the controller, the proposed method is applied to the trajectory control of the two-link manipulator.

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신경회로망 직접 적응제어 및 안정성 해석 (Neural Direct Adaptive Control and Stability Analysis)

  • 최종수;김형석;김성중;권오신
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 하계학술대회 논문집 B
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    • pp.1179-1181
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    • 1996
  • In this paper, method for direct adaptive control of discrete nonlinear systems using neural network is presented. Also, the stability problems are investigated in sense of the Lyapunov stability conditions. Through extensive simulation, the SOON is shown to be effective for indirect adaptive control of nonlinear dynamic systems.

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Sliding Mode Control with Fixed Switching Frequency for Four-wire Shunt Active Filter

  • Hamoudi, Farid;Chaghi, A. Aziz;Amimeur, Hocine;Merabet, El Kheir
    • Journal of Electrical Engineering and Technology
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    • 제6권5호
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    • pp.647-657
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    • 2011
  • The present paper proposes a sliding mode control with fixed switching frequency for three-phase three-leg voltage source inverter based four-wire shunt active power filter. The aim is to improve phase current waveform, neutral current mitigation, and reactive power compensation in electric power distribution system. The performed sliding mode for active filter current control is formulated using elementary differential geometry. The discrete control vector is deduced from the sliding surface accessibility using the Lyapunov stability. The problem of the switching frequency is addressed by considering hysteresis comparators for the switched signals generation. Through this method, a variable hysteresis band has been established as a function of the sliding mode equivalent control and a predefined switching frequency in order to keep this band constant. The proposed control has been verified with computer simulation which showed satisfactory results.

시변 시간지연을 가지는 입력제한 시스템의 모델예측제어 (Model Predictive Control for Input Constrained Systems with Time-varying Delay)

  • 이상문
    • 전기학회논문지
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    • 제61권7호
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    • pp.1019-1023
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    • 2012
  • This paper considers a model predictive control problem of discrete-time constrained systems with time-varying delay. For this problem, a delay dependent state feedback control approach is used to achieve asymptotic stabilization of systems with input constraints. Based on Lyapunov stability theory, a new stability condition is obtained via linear matrix inequality formulation to find cost monotonicity condition of the model predictive control algorithm which guarantee the closed loop stability. Finally, the proposed method is applied to a numerical example in order to show the effectiveness of our results.