• Title/Summary/Keyword: adaptive feedforward control

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Adaptive Control of Permanent Magnet Linear Synchronous Motor using Wavelet Transform (Wavelet 변환을 이용한 PMLSM의 적응제어)

  • Lee June;Lee Jin Woo;Suh Jin Ho;Lee Young Jin;Lee Kwon Soon
    • Proceedings of the KIEE Conference
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    • summer
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    • pp.956-958
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    • 2004
  • 이 논문에서, 우리는 PMLSM(permanent magnet linear synchronous motor) 시스템에서 발생하는 detent force의 ripple 저감을 위한 진동보상 모델과 제안한 구조에 대한 제어기 설계 방법을 제시한다. 본 논문에서 고려되어진 제어기는 feedforward 보상기, PID feedback 보상기, 그리고 adaptive feedforward 보상기의 세 부분으로 구성된 제어기를 사용한다. 특히, PMLSM의 위치 정밀성 향상에 관한 연구를 위한 정밀 위치 제어의 문제는 PM으로 인해 발생하는 detent force이며, 이를 해결하기 위해 출력신호를 웨이블릿 변환하여 추출 후 이를 보상하였다.

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Robust Decentralized Adaptive Controller for Trajectory Tracking Control of Uncertain Robotic Manipulators (비중앙 집중식 강성 적응 제어법을 통한 산업용 로봇 궤도추적제어)

  • 유삼상
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.30 no.4
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    • pp.329-340
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    • 1994
  • This paper presents a dynamic compensation methodology for robust trajectory tracking control of uncertain robot manipulators. To improve tracking performance of the system, a full model-based feedforward compensation with continuous VS-type robust control is developed in this paper(i.e,. robust decentralized adaptive control scheme). Since possible bounds of uncertainties are unknown, the adaptive bounds of the robust control is used to directly estimate the uncertainty bounds(instead of estimating manipulator parameters as in centralized adaptive control0. The global stability and robustness issues of the proposed control algorithm have been investigated extensively and rigorously via a Lyapunov method. The presented control algorithm guarantees that all system responses are uniformly ultimately bounded. Thus, it is shown that the control system is evaluated to be highly robust with respect to significant uncertainties.

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Study of Adaptive Learning Control for Robot-Manipulator (로봇 매니퓰레이터의 적응학습제어에 관한 연구)

  • 최병현;국태용;최혁렬
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1996.11a
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    • pp.396-400
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    • 1996
  • It is prerequisite to apply dynamics controller to control robot manipulator required to perform fast and Precise motion. In this Paper, we Propose an adaptive 3earning control method for the dynamic control of a robot manipulator. The proposed control scheme is made up of PD controller in the feedback loop and the adaptive learning controller in the feedforward loop. This control scheme has the ability to estimate uncertain dynamic parameters included intrinsically in the system and to achieve the desired performance without the nasty matrix operation. The proposed method is applied to a SCARA robot and experimentally verified.

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ROBUST ADAPTIVE CONTROLLER FOR ROBOT MANIPULATOR CONTROL (로보트 매니플레이터를 위한 강인한 제어기 설계에 관한 연구)

  • Ryoo, Kgi-Wung;Hong, Suk-Kyo
    • Proceedings of the KIEE Conference
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    • 1989.11a
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    • pp.456-461
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    • 1989
  • In this paper, the robust adaptive controller for the accurate position control of the robot manipulator in discribed. The proposed controller has feedforward and feedback terms. To reduced the cumputation time, the inertia matrix is simlipied by diagonal matrix and the centrifugal and Colioris term and gravity term are assumed to be zero. The auxiliary signal is added in the controller. This signal improve convergence time of error. The simulation results show that the proposed method is applied to the real time control.

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Adaptive Control for Trajectory Tracking of a Manipulator with Pneumatic Artificial Muscle Actuators (공압인공근육로봇의 궤적추종의 적응제어)

  • Park, H.W.;Park, N.C.;Yang, H.S.;Park, Y.P.
    • Journal of the Korean Society for Precision Engineering
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    • v.14 no.5
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    • pp.100-107
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    • 1997
  • A pneumatic artificial muscle type of actuator, which acts similar to human muscle, is developed recently. In this paper, an adaptive controller is presented for the trajectory tracking problem of a two-degree- of-freedom manipulator using two pairs of pneumatic artificial muscle actuators. Due to the nonlinearity and the uncertainty on the dynamics of the actuator, it is difficult to make the effective control schemes of this system. By the adaptive control law which inclueds a nonlinear "feedforward" term compensating paramet- ric uncertainties in addition to P.I.D. scheme, both golbal stability of the system and convergence of the tracking error are guaranted. The effectiveness of the proposed control method for the manipulator using this actuator is illustrated through experiments.periments.

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Design of a real time adaptive controller for industrial robot using TMS320C31 chip (TMS320C31칩을 사용한 산엽용 로보트의 실시간 적응 제어기 설계)

  • Han, S.H.;Kim, Y.T.;Lee, M.H.;Kim, S.K.;Kim, J.O.
    • Journal of the Korean Society for Precision Engineering
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    • v.13 no.10
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    • pp.94-104
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    • 1996
  • This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C31) for robotic manpulators to achieve accurate trajectory tracking by the joint angles Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed contorl scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Morever, this scheme does not require an accurate dynamic modeling nor values of manpipulator parameters and payload. Performance of the adaptive controller is illustated by simulation and experimental results for a SCARA robot.

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Design of an Intelligent Speed Control System for Marine Diesel Engines (선박용 디젤엔진을 위한 지능적인 속도제어시스템의 설계)

  • J.S.Ha;S.J.Oh
    • Journal of Advanced Marine Engineering and Technology
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    • v.21 no.4
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    • pp.414-420
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    • 1997
  • An intelligent speed control system for marine diesel engines is presented. The approach adopt¬ed is to use a conventional PID controller for normal operation and a feedforward controller for adaptive control. The feedforward controller is a neural network. The neural network is the inverse dynamics model of the plant, which is being trained on line. The parametric model of the diesel engine is represented in a linear second-order system, with a first-order combustion part and a revolution part each at a normal operating point. The time delay in the control of the com¬bustion part is approximated to the first-order system. The tuned PID parameters are set based on the model for normal operating point. To obtain the inverse dynamics of the diesel engine system, two neural networks are used, one for inverse, the other for forward dynamics. The former is posi¬tioned across the plant to learn its inverse dynamics during operation, and the latter is placed in series with the controlled plant. Simulation results are presented to illustrate the applicability of the proposed scheme to intelligent adaptive control of diesel engines.

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Disturbance Compensation Control of An Active Magnetic Bearing System by Multiple FXLMS Algorithm - Theory (MFXLMS 알고리즘을 이용한 전자기배어링계의 외란 보상 제어기 - 이론)

  • 강민식;정종수
    • Journal of the Korean Society for Precision Engineering
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    • v.21 no.2
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    • pp.74-82
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    • 2004
  • In this paper, a disturbance feedforward compensator design technique is proposed for an active magnetic bearing system subject to base motion for attenuating disturbance responses. In the consideration of the requirements on the model accuracy in the model based compensator designs, an experimental feedforward compensator design based on adaptive estimation by means of the Multiple Filtered-x least mean square(MFXLMS) algorithm is proposed. The performance and the effectiveness of the proposed technique will be presented in the succeeding paper in which the proposed technique is applied to a 2-DOF active magnetic bearing system subject to base motion.

A Direct Adaptive Fuzzy Control of Nonlinear Systems with Application to Robot Manipulator Tracking Control

  • Cho, Young-Wan;Seo, Ki-Sung;Lee, Hee-Jin
    • International Journal of Control, Automation, and Systems
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    • v.5 no.6
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    • pp.630-642
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    • 2007
  • In this paper, we propose a direct model reference adaptive fuzzy control (MRAFC) for MIMO nonlinear systems whose structure is represented by the Takagi-Sugeno fuzzy model. The adaptive law of the MRAFC estimates the approximation error of the fuzzy logic system so that it provides asymptotic tracking of the reference signal for the systems with uncertain or slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal. To verify the validity and effectiveness of the MRAFC scheme, the suggested analysis and design techniques are applied to the tracking control of robot manipulator and simulation studies are carried out. In the control design, the MRAFC is combined with feedforward PD control to make the actual joint trajectories of the robot manipulator with system uncertainties track the desired reference joint position trajectories asymptotically stably.