• 제목/요약/키워드: feedforward/feedback controller

검색결과 178건 처리시간 0.031초

신경 회로망을 이용한 유연한 축을 갖는 5절 링크 로봇 메니퓰레이터의 모델링 (Modeling of a 5-Bar Linkage Robot Manipulator with Joint Flexibility Using Neural Network)

  • 이성범;김상우;오세영;이상훈
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.431-431
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    • 2000
  • The modeling of 5-bar linkage robot manipulator dynamics by means of a mathematical and neural architecture is presented. Such a model is applicable to the design of a feedforward controller or adjustment of controller parameters. The inverse model consists of two parts: a mathematical part and a compensation part. In the mathematical part, the subsystems of a 5-bar linkage robot manipulator are constructed by applying Kawato's Feedback-Error-Learning method, and trained by given training data. In the compensation part, MLP backpropagation algorithm is used to compensate the unmodeled dynamics. The forward model is realized from the inverse model using the inverse of inertia matrix and the compensation torque is decoupled in the input torque of the forward model. This scheme can use tile mathematical knowledge of the robot manipulator and analogize the robot characteristics. It is shown that the model is reasonable to be used for design and initial gain tuning of a controller.

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역히스테리시스 모델과 PID-신경회로망 제어기를 이용한 압전구동기의 정밀 위치제어 (Precision Position Control of Piezoactuator Using Inverse Hysteresis Model and Neuro-PID Controller)

  • 김정용;이병룡;양순용;안경관
    • 제어로봇시스템학회논문지
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    • 제9권1호
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    • pp.22-29
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    • 2003
  • A piezoelectric actuator yields hysteresis effect due to its composed ferroelectric. Hysteresis nonlinearty is neglected when a piezoelectric actuator moves with short stroke. However when it moves with long stroke and high frequency, the hysteresis nonlinearty can not be neglected. The hysteresis nonlinearty of piezoelectric actuator degrades the control performance in precision position control. In this paper, in order to improve the control performance of piezoelectric actuator, an inverse modeling scheme is proposed to compensate the hysteresis nonlinearty. And feedforward - feedback controller is proposed to give a good tracking performance. The Feedforward controller is an inverse hysteresis model, base on neural network and the feedback control is implemented with PID control. To show the feasibility of the proposed controller and hysteresis modeling, some experiments have been carried out. It is concluded that the proposed control scheme gives good tracking performance.

Superheat Control of an Inverter-driven Heat Pump Using PI Control Algorithm

  • Park, Jong-Min;Kim, Yong-Chan
    • International Journal of Air-Conditioning and Refrigeration
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    • 제10권2호
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    • pp.106-115
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    • 2002
  • The performance of an inverter-driven water-to-water heat pump with an electronic expansion valve (EEV) was measured as a function of compressor frequency, load conditions, and EEV opening. Based on the test results, a controller using proportional integral (PI) feedback or PI feedforward algorithm was designed and tested to investigate capacity modulation and transient response control of the system. Although the relation between superheat and EEV opening of the heat pump showed nonlinear characteristics, a control gain obtained at the rated frequency was applicable to various operating conditions without causing large deviations. When the simple PI feedback control algorithm was applied, a large overshoot of superheat and wet compression were observed due to time delay effects of compressor frequency. However, applying PI feedforward control scheme yielded better system performance and higher reliability, compared to the PI feedback algorithm.

주파수 영역 모델 방법을 이용한 평판 구조물의 능동 소음전달 제어 (Active Noise Transmission Control Through a Panel Structure Using a Frequency Domain Identification Method)

  • 김영식;김인수;문찬영
    • 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.

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진화 연산 알고리즘과 퍼지 논리를 이용한 고속 열처리 공정기의 제어기 설계 (Design of Controller for Rapid Thermal Process Using Evolutionary Computation Algorithm and Fuzzy Logic)

  • 황민웅;도현민;최진영
    • 한국지능시스템학회논문지
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    • 제8권6호
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    • pp.37-47
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    • 1998
  • 본 논문은 진화 연산 알고리즘과 퍼지 로직을 이용하여 고속 열처리 공정기의 웨이퍼 온도를 제어하는 제어기 설계 방법을 제안한다. 전체 제어기는 기준 온도의 정상 상태의 추종을 위한 앞먹임 정적 제어기, 과도 상태의 추종을 위한 앞먹임 동적 제어기, 그리고 온라인 상에서 모델링 오차나 외란을 극복하기 위한 되먹임 오차 제어기로 구성된다. 앞먹임 제어기들은 퍼지 로직을 이용하여 모든 동작점에서 제어 입력을 구해주는 전역적 비선형 제어기로 구성된다. 각 제어기들의 제어 파라미터는 진화 연산 알고리즘을 이용하여 추정되므로 수학적 모델식을 모르는 경우에도 제어기를 설계할 수 있는 장점이 있다. 끝으로 모의 실험을 통하여 제어기의 성능을 검증한다.

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다층 신경 회로망을 이용한 굴삭기의 위치 제어 (The Position Control of Excavator's Attachment using Multi-layer Neural Network)

  • 서삼준;권대익;서호준;박귀태;김동식
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1995년도 하계학술대회 논문집 B
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    • pp.705-709
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    • 1995
  • The objective of this study is to design a multi-layer neural network which controls the position of excavator's attachment. In this paper, a dynamic controller has been developed based on an error back-propagation(BP) neural network. Since the neural network can model an arbitrary nonlinear mapping, it was used as a commanded feedforward input generator. A PD feedback controller is used in parallel with the feedforward neural network to train the system. The neural network was trained by the current state of the excavator as well as the PD feedback error. By using the BP network as a feedforward controller, no a priori knowledge on system dynamics is need. Computer simulation results demonstrate such powerful characteristics of the proposed controller as adaptation to changing environment, robustness to disturbancen and performance improvement with the on-line learning in the position control of excavator attachment.

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신경회로망을 이용한 대부하 표적지향 시스템 제어 (Control of a Heavy Load Pointing System Using Neural Networks)

  • 김병운;강이석
    • 한국정밀공학회지
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    • 제21권5호
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    • pp.55-63
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    • 2004
  • This paper presents neural network based controller using the feedback error loaming technique for a heavy load pointing system. Also the mathematical model was developed to analyze heavy load pointing system. The control scheme consists of a feedforward neural network controller and a fixed-gain feedback controller. This neural network controller is trained so as to make the output of the feedback controller zero. The proposed controller is compared with the conventional PI controller through simulations, and the results show that the pointing accuracy of the proposed control system are improved against the disturbance induced by vehicle running on the bump course.

UPS 용 3상 인버터의 LC필터단 출력전압 제어 방식 비교연구 (A Comparative Study on the Output Voltage Control Strategies of Three Phase Inverter with LC Filter for UPS)

  • 나운기;김태완;정승기
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 하계학술대회 논문집 A
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    • pp.312-317
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    • 1996
  • This paper compares the output voltage control strategies of three-phase PWM inverter for uninterruptible power supply. The feedforward control, feedforward/feedback control, and decoupled feedback control in both the synchronous reference frame and the stationary reference frame are examined. In particular, it is shown that the response of the decoupled feedback controller in the synchronous reference frame can be improved by pole-zero cancellation method. It is also shown that the pole-zero cancellation method reduces to the deadbeat control, when it is implemented with digital controller.

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인공신경망 Feedforward제어기를 이용한 좌심실보조장치의 제어실험 (Control of Left Ventricular Assist Device using Neural Network Feedback Feedforward Controller)

  • 정성택;류정우;김상현
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1997년도 춘계학술대회 논문집
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    • pp.150-155
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    • 1997
  • In this paper,we present neural network for control of Left Ventricular Assist Device(LVAD)system with a pneumatically driven mock cirulation system. It is necessary to apply high perfomance control techniques, since the LVAD system represent nonlinear and time-varing characteristics. Fortunately, the neural network can be applied to control of a nonliner dynamic system by learning capability. In this study,we identify the LVAD system with neural network and control the LVAD system by PID controller and neural network feedforward controller. The ability and effectiveness of controlling the LVAD system using the proposed algorithm will be demonstrated by computer simulation and experiment.

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힐버트 변환을 이용한 주기적인 외란 및 잡음제거 (PERIODIC DISTURBANCE AND NOISE REJECTION METHOD USING HIRBERT TRANSFORM)

  • 나희승;박영진
    • 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.

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