• 유공압시스템학회논문집
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• 제7권3호
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• pp.1-6
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• 2010

This paper deals with the issue of simple adaptive position control for a pump-controlled cylinder system. A fixed displacement pump is utilized instead of servo valve and its speed is controlled by AC motor. The whole control system is composed of a pair of interconnected subsystems, that is, a feedback control system and a feedforward control system. From experiments it is shown that position control using simple adaptive control can accomplish significant reduction in position tracking error comparing to a conventional PID control.

• 한국정밀공학회지
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• 제18권9호
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• pp.71-81
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• 2001

This paper analyzes the effectiveness of minimizing vibration and sound transmission on/through a thin rectangular plate by both feedback control and hybrid control which combines adaptive feedforward control with a feedback loop. An experimental system identification technique using the matrix-fractional curve-fitting of the frequency response data is introduced for complex shaped structures. This identification technique reduces the model order o the MIMO(Multi-Input Multi-Output) system which simplifies the practical implementation. The adaptive feedforward control uses a Multiple filtered-x LMS(Least Mean Square) algorithm and the feedback control uses a multivariable digital LQG(Linear Quadratic Gaussian) algorithm. Experimental results show that an effective reduction of sound transmission is achieved by the hybrid control scheme when both vibration and noise measurement signals are incorporated in the controller.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 추계학술대회논문집
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• pp.443-448
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• 2000

In this paper, we propose a novel adaptive feedforward controller for periodic disturbance and noise cancellation, with a frequency tracking capability. It can be added to an existing feedback control system without altering the original closed-loop characteristics, which is based on adaptive algorithm. We introduce novel algorithm "Constrained AFC(adaptive feedforward controller) algorithm" that increase the convergence region regardless of the delay in the closed loop system. In the algorithms, coefficients of the controller are adapted using the residuals of constrained structure which are defined in such a way that the coefficients become time invariant. The proposed algorithm not only estimate the magnitude and phase of the tonal disturbance and noise but also track the frequency of the tone, which changes in quasi-static manner. The frequency tracking algorithm uses the instantaneous frequency approach based on Hilbert transform. A number of computer simulations have been carried out in order to demonstrate the effectiveness of proposed method under various conditions.

• 한국자동차공학회논문집
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• 제2권6호
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• pp.29-37
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• 1994

Active noise control of random noise which propatate in the vehicle cabin as a form of spherical wave is the target of this study. In the previous study, the adaptive algorithm for adaptive controller is presented for the application in active noise control system. And for the preliminary study of adaptive active noise control in vehicle cabin as a real system, a computer simulation is performed on the effectiveness of the adaptive algorithm in the amplitude of the pressure fluctuation. This work studies the implementation of multi-channel feedforward adaptive algorithm for the reduction of the noise inside a vehicle cabin using a number of secondary sources derived by adaptive filtering of reference noise source. Multi-channel adaptive feedforward algorithm are verified in numerical simulation and semi-experimental justification of developed system is made on a domestic passenger car. In the results of semi-experimental study, the noise of specific region in the interior of automobile are reduced for the appreciabe sound pressure level in the operating engine rpm and finally this study suggests the capabilities of the real time active noise control in 3 dimensional acoustic fields.

• 한국전자파학회논문지
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• 제15권2호
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• pp.127-133
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• 2004

피드포워드 증폭기는 선형화 성능이 우수하고 선형화 대역폭이 넓은 장점이 있다. 그러나 피드포워드 증폭기는 다양한 소자들로 구성되는 개루프 시스템이기 때문에 주변 환경의 변화에 의해서 성능 저하가 일어나기 쉽다. 따라서 피드포워드 증폭기가 허용하는 범위 내에서 원하는 성능을 유지하기 위해서는 선형화 루프의 이득과 위상을 조정하기 위한 제어 방법이 필요하다. 본 논문에서는 steepest descent 알고리즘을 이용한 새로운 적응형 제어 방법을 제안하였다. 제안한 방법은 기존의 제어 방법에 비해 수렴 속도가 빠르고 구현하기가 쉬운 장점이 있음을 시뮬레이션을 통해 확인하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.997-1001
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• 2000

In this paper, the case studies of reducing rotational errors is theoretically done for a grinding spindle with an active magnetic bearing system. The rotational errors acting on the magnetic bearing spindle are due to mass unbalance of rotor, runout, grinding excitation and unmodeled nonlinear dynamics of electromagnets. For the most case, the electrical runout of sensor target is big even in well finished surface, this runout can cause a rotation error amplified by feedback control system. The adaptiveed forward method based on LMS algorithm is discussed to compensate this kind of runout effects, and investigated its effectiveness by numerical simulation and experimental analysis. The electrical runout form the rear sensor target of grind spindle is about 70$\mu\textrm{m}$ with harmonic frequencies. The rotor orbit size in rear bearing is reduced about to 5$\mu\textrm{m}$ due to 1X and 2X rejection by feedforward control.

• Journal of Electrical Engineering and information Science
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• 제2권6호
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• pp.82-89
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• 1997

In this paper, an adaptive speed controller with an FNN(Feedforward Neural Network) is proposed for servo motor drives. Generally, the motor system has nonlinearities in friction, load disturbance and magnetic saturation. It is necessary to treat the nonlinearities for improving performance in servo control. The FNN can be applied to control and identify a nonlinear dynamical system by learning capability. In this study, at first, a robust speed controller is developed by Lyapunov stability theory. However, the control input has discontinuity which generates an inherent chattering. To solve the problem and to improve the performances, the FNN is introduced to convert the discontinuous input to continuous one in error boundary. The FNN is applied to identify the inverse dynamics of the motor and to control the motor using coordination of feedforward control combined with inverse motor dynamics identification. The proposed controller is developed for an SR motor which has highly nonlinear characteristics and it is compared with an MRAC(Model Reference Adaptive Controller). Experiments on an SR motor illustrate te validity of the proposed controller.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 춘계학술대회 논문집
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• pp.1011-1015
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• 2000

In this paper, the case studies of reducing rotational errors is theoretically done for a grinding spindle with an active magnetic bearing system. The rotational errors acting on the magnetic bearing spindle are due to mass unbalance of rotor, runout, grinding excitation and unmodeled nonlinear dynamics of electromagnets. The adaptive feedforward method based on LMS algorithm is discussed to compensate output and input disturbances, and investigated its effectiveness by numerical simulation. The feedforward control reduced external excitation and rotational error for specified frequency. The interpolation method using impulse function for cancelling the electrical 'uncut is studied. These methods show their effectiveness for the rotational accuracy of the improving magnetic bearing spindle through some simulation results of the rotational error decreased by them.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.79-82
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• 2002

In this paper, we propose an adaptive repetitive control algorithm for the system the task of which is repetitive. The feedforward controller in the repetitive control system is modified by using the system parameter identifier in order to improve the convergence characteristics. The proposed algorithm is applied to the tracking control of a linear BLDC motor to which a periodic reference input is applied. It is illustrated by simulation results that the proposed adaptive repetitive control method yields better control performance than existing repetitive control even when modeling errors exist.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.150-155
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• 1993

The neural network MRAC system is presented. The purpose of this paper is applied to a plant that is to be controlled in a strongly nonlinear environment. The proposed system has a learning and adaptive ability in the varying environment by using the back-propagation learning algorithm based on Lyapunov stability theory. N.N. regulator is a part of overall system and is guaranteed to be stable in initial stage. Nonlinear terms of the varying mass, colilori, centifugal, and gravity are compensated for by feedforward N.N. regulator. And the feedback controller (adaptive mechanism) works to eliminate errors of position, velocity which the feedforward controller cannot compensate for. Finally, the proposed system will be demonstrated by simulation of a two d.o.f robot manipulator.