• 제목/요약/키워드: electronic stability control

검색결과 512건 처리시간 0.025초

Periodic Sampled-Data Control for Fuzzy Systems;Intelligent Digital Redesign Approach

  • Kim, D.W.;Joo, Y.H.;Park, J.B.
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.1492-1495
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    • 2005
  • This paper presents a new linear-matrix-inequality-based intelligent digital redesign (LMI-based IDR) technique to match the states of the analog and the digital T-S fuzzy control systems at the intersampling instants as well as the sampling ones. The main features of the proposed technique are: 1) the affine control scheme is employed to increase the degree of freedom; 2) the fuzzy-model-based periodic control is employed; and the control input is changed n times during one sampling period; 3) The proposed IDR technique is based on the approximately discretized version of the T-S fuzzy system; but its discretization error vanishes as n approaches the infinity. 4) some sufficient conditions involved in the state matching and the stability of the closed-loop discrete-time system can be formulated in the LMIs format.

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ADAPTIVE SLICING ODE CONTROL USING FUZZY LOGIC SYSTEM

  • Yoo, Byungkook;Jeoung, Sacheul;Ham, Woonchul
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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    • pp.26-30
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    • 1995
  • In this study, the fuzzy approximator and sliding mode control (SMC) scheme are considered. An adaptive sliding mode control is proposed based on the SMC theory. This proposed control scheme is that a adaptive law is utilized to approximate the unknown function f by fuzzy logic system in designing the sliding mode controller for the nonlinear system. In order to reduce the approximation errors, the differences of nonlinear function and fuzzy approximator, an adaptive law is also intoduced and the stability of proposed control scheme are proven with simple adaptive law and roburst adaptive law. This proposed control scheme is applied to a single link robot arm.

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부정합조건 외란을 갖는 비선형 시스템의 퍼지 외란 관측기 기반 다중 슬라이딩 평면 제어 (Fuzzy Disturbance Observer based Multiple Sliding Surface Control of Nonlinear Systems with Mismatched Disturbance)

  • 이상윤;서형근;현창호;박민용
    • 한국지능시스템학회논문지
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    • 제24권4호
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    • pp.385-391
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    • 2014
  • 본 논문은 부정합조건 외란을 갖는 비선형 시스템을 제어하기 위하여 퍼지 외란 관측기 기반 다중 슬라이딩 평면 제어 기법을 제안한다. 부정합조건에서도 제어 대상이 평형점으로 수렴할 수 있도록 다중 슬라이딩 평면 기법을 사용하여 제어기를 설계한다. 더불어, 퍼지 외란 관측기를 도입함으로써 다중 슬라이딩 평면 제어의 문제점인 항의 복잡성 (Explosion of terms)을 해결하고, 기존 슬라이딩 모드 제어 상에서 불연속 신호를 사용해서 일어나는 채터링(Chattering)을 제거한다. 제안된 시스템의 안정성은 리아프노브 안정성 이론을 이용하여 증명한다. 제안한 방법의 성능 우수성을 보이기 위해 모의실험을 통하여 비선형 외란 관측기 기반 슬라이딩 모드 제어기의 성능과 비교 분석한다.

후륜 조향각 결정을 통한 통합 섀시 제어기의 성능 향상 (Performance Improvement of Integrated Chassis Control with Determination of Rear Wheel Steering Angle)

  • 임성진
    • 대한기계학회논문집A
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    • 제41권2호
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    • pp.111-119
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    • 2017
  • 본 논문은 자세 제어 장치(ESC)와 후륜 조향 장치(RWS)를 장착한 통합 섀시 제어기의 성능을 향상시키기 위해 후륜 조향각을 결정하는 방법을 제안한다. 차량을 안정화시키기 위해 필요한 제어 요 모멘트는 자세 제어 장치와 후륜 조향 장치를 이용하여 만들어진다. 각 장치의 타이어 힘을 결정하기 위해 의사역행렬 제어할당 방법을 적용한다. 제어기의 성능을 향상시키기 위해 후륜 조향 장치의 조향각을 결정하는 데에 네 가지 방법을 적용한다. 차량 시뮬레이션 패키지인 CarSim에서 시뮬레이션을 수행하여 제안된 방법들이 통합 섀시 제어기의 성능을 향상시킬 수 있음을 검증한다.

타이어 횡력 제한 조건 하에서 ESC와 AFS를 이용한 통합 섀시 제어 (Unified Chassis Control with ESC and AFS under Lateral Tire Force Constraint on AFS)

  • 임성진;남기홍;이호석
    • 제어로봇시스템학회논문지
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    • 제21권7호
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    • pp.595-601
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    • 2015
  • This paper presents an unified chassis control with electronic stability control (ESC) and active front steering (AFS) under lateral force constraint on AFS. When generating the control yaw moment, an optimization problem is formulated in order to determine the tire forces, generated by ESC and AFS. With Karush-Kuhn-Tucker optimality condition, the optimum tire forces can be algebraically calculated. On low friction road, the lateral force in front wheels is easily saturation. When saturated, AFS cannot generate the required control yaw moment. To cope with this problem, new constraint on the lateral tire force is added into the original optimization problem. To check the effectiveness of the propose method, simulation is performed on the vehicle simulation package, CarSim.

The Seek Control Design with Gain-Scheduling in Hard Disk Drives

  • Hwang, Eun-Ju;Hyun, Chang-Ho;Park, Mig-Non
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제11권1호
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    • pp.65-70
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    • 2011
  • The increased disk rotational velocity to improve the data transfer rate has raised up many serious problems in its servo control system which should control the position and velocity of a spot relative to a rotating disk. This paper proposes gain-scheduling-based track-seek control for single stage actuator of hard disk drives. Gain scheduling is a technique that can extend the validity of the linearization approach to a range of operating points and one of the most popular approaches to nonlinear control design. The proposed method schedules controller gains to improve the transient response and minimize overshoot during the functions of the read/write head positioning servomechanism for the seek control. The validity of the proposed method is demonstrated through stability analysis and simulation results.

Intelligent Gain and Boundary Layer Based Sliding Mode Control for Robotic Systems with Unknown Uncertainties

  • Yoo, Sung-Jin;Park, Jin-Bae;Choi, Yoon-Ho
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.2319-2324
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    • 2005
  • This paper proposes a intelligent gain and boundary layer based sliding mode control (SMC) method for robotic systems with unknown model uncertainties. For intelligent gain and boundary layer, we employ the self recurrent wavelet neural network (SRWNN) which has the properties such as a simple structure and fast convergence. In our control structure, the SRWNNs are used for estimating the width of boundary layer, uncertainty bound, and nonlinear terms of robotic systems. The adaptation laws for all parameters of SRWNNs and reconstruction error bounds are derived from the Lyapunov stability theorem, which are used for an on-line control of robotic systems with unknown uncertainties. Accordingly, the proposed method can overcome the chattering phenomena in the control effort and has the robustness regardless of unknown uncertainties. Finally, simulation results for the three-link manipulator, one of the robotic systems, are included to illustrate the effectiveness of the proposed method.

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Stable Predictive Control of Chaotic Systems Using Self-Recurrent Wavelet Neural Network

  • Yoo Sung Jin;Park Jin Bae;Choi Yoon Ho
    • International Journal of Control, Automation, and Systems
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    • 제3권1호
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    • pp.43-55
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    • 2005
  • In this paper, a predictive control method using self-recurrent wavelet neural network (SRWNN) is proposed for chaotic systems. Since the SRWNN has a self-recurrent mother wavelet layer, it can well attract the complex nonlinear system though the SRWNN has less mother wavelet nodes than the wavelet neural network (WNN). Thus, the SRWNN is used as a model predictor for predicting the dynamic property of chaotic systems. The gradient descent method with the adaptive learning rates is applied to train the parameters of the SRWNN based predictor and controller. The adaptive learning rates are derived from the discrete Lyapunov stability theorem, which are used to guarantee the convergence of the predictive controller. Finally, the chaotic systems are provided to demonstrate the effectiveness of the proposed control strategy.

A Realization Method of Fault-tolerant Control of Flexible Arm under Sensor Fault by Using an Adaptive Sensor Signal Observer

  • Izumikawa Yu;Yubai Kazuhiro;Hirai Junji
    • Journal of Power Electronics
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    • 제6권1호
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    • pp.8-17
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    • 2006
  • In this paper, we propose a fault-tolerant control system for the position control and vibration suppression of a flexible arm robot. The proposed control system has a strain gauge sensor signal observer based on a reaction force observer and detects a fault by monitoring an estimated error. In order to improve the estimation accuracy, the plant parameters included in the sensor signal observer are updated by using the strain gauge sensor signal in normal time through the adaptive law. After fault detection, the proposed control system exchanges the faulty sensor signal for the estimated one and switches to a fault mode controller so as to maintain the stability and the control performance. We confirmed the effectiveness of the proposed control system through several experiments.

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.