• Title/Summary/Keyword: Inverse Dynamic Model

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Design of Recurrent Time Delayed Neural Network Controller Using Fuzzy Compensator (퍼지 보상기를 사용한 리커런트 시간지연 신경망 제어기 설계)

  • 이상윤;한성현;신위재
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2002.04a
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    • pp.463-468
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    • 2002
  • In this paper, we proposed a recurrent time delayed neural network controller which compensate a output of neural network controller. Even if learn by neural network controller, it can occur an bad results from disturbance or load variations. So in order to adjust above case, we used the fuzzy compensator to get an expected results. And the weight of main neural network can be changed with the result of learning a inverse model neural network of plant, so a expected dynamic characteristics of plant can be got. As the results of simulation through the second order plant, we confirmed that the proposed recurrent time delayed neural network controller get a good response compare with a time delayed neural network controller.

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Cracked rotor diagnosis by means of frequency spectrum and artificial neural networks

  • Munoz-Abella, B.;Ruiz-Fuentes, A.;Rubio, P.;Montero, L.;Rubio, L.
    • Smart Structures and Systems
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    • v.25 no.4
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    • pp.459-469
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    • 2020
  • The presence of cracks in mechanical components is a very important problem that, if it is not detected on time, can lead to high economic costs and serious personal injuries. This work presents a methodology focused on identifying cracks in unbalanced rotors, which are some of the most frequent mechanical elements in industry. The proposed method is based on Artificial Neural Networks that give a solution to the presented inverse problem. They allow to estimate unknown crack parameters, specifically, the crack depth and the eccentricity angle, depending on the dynamic behavior of the rotor. The necessary data to train the developed Artificial Neural Network have been obtained from the frequency spectrum of the displacements of the well- known cracked Jeffcott rotor model, which takes into account the crack breathing mechanism during a shaft rotation. The proposed method is applicable to any rotating machine and it could contribute to establish adequate maintenance plans.

Neurointerface Using an Online Feedback-Error Learning Based Neural Network for Nonholonomic Mobile Robots

  • Lee, Hyun-Dong;Watanabe, Keigo;Jin, Sang-Ho;Syam, Rafiuddin;Izumi, Kiyotaka
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.330-333
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    • 2005
  • In this study, a method of designing a neurointerface using neural network (NN) is proposed for controlling nonholonomic mobile robots. According to the concept of virtual master-slave robots, in particular, a partially stable inverse dynamic model of the master robot is acquired online through the NN by applying a feedback-error learning method, in which the feedback controller is assumed to be based on a PD compensator for such a nonholonomic robot. A tracking control problem is demonstrated by some simulations for a nonholonomic mobile robot with two-independent driving wheels.

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A study on robust multivariable control of stewart platform type motion simulator (스튜어트 플랫폼 방식 운동재현기의 다변수 견실제어에 관한 연구)

  • 정규홍;박철규;이교일
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10a
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    • pp.736-741
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    • 1992
  • The Stewart platform is one example of a motion simulator which generates 6 DOF motion in space by 6 actuators connected in parallel. The present SISO controllers are designed to track displacement command of each actuator computed from reference 6 DOF motion of platform by Stewart platform inverse kinematics. But this type of control can't cope with external load variation, geometric configuration of motion simulator, and different dynamic behavior of 6 DOF motion. In this paper, a multivariable controller using H- optimal control theory is designed for linerized simulator model with each actuator driving force as control input and platform 6 DOF motion as measured output. Nonlinear simulation result of the H$_{\infty}$ MIMO controller is not satisfied in steady-state characteristics. But the proposed H$_{\infty}$ + PI control scheme shows acceptable performance.e.e.

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A study on the analysis and design for VTR deck mechanisms using CAE (CAE를 이용한 VTR Deck기구의 해석 및 설계)

  • 박태원;범진환;한형석;김명규;김광배
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.17 no.1
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    • pp.223-235
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    • 1993
  • VTR(Video Tape Recorder) has very complicated mechanisms composed of various cams, links, gears and so on. To satisfy kinematic requirements of VTR components, various geometric constraints between rigid bodies and a translational cam design program are developed. Mechanisms of VTR are divided into functional groups like a control part, a loading part and a tape guide part. Each group is modeled for kinematic and dynamic analysis. Finally, all groups are combined together for a complete VTR model and loads required for each function of VTR controls are studied. Detailed description of developed programs are presented and result are discussed.

A Lane-change Collision Avoidance Algorithm for Autonomous Vehicles and HILS(Hardware-In-the-Loop Simulation) Test (자율주행 차량의 충돌회피 차선변경 제어 알고리즘 개발과 HILS 시험)

  • 류제하;김종협
    • Transactions of the Korean Society of Automotive Engineers
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    • v.7 no.5
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    • pp.240-248
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    • 1999
  • This paper presents a lane-change collision avoidance control algorithm for autonomous vehicles that will be used in AHS(Automated Highway System). In the proposed control algorithm, nominal control inputs are generated by solving the inverse vehicle dynamic equations of motion for a lane-change maneuver. In addition, a corrective steering input from preview as well as DYC (Direct Yaw Moment Control) may be included to reduce unpredictable errors and to insure yaw directional stability, respectively. The performance of the algorithm is evaluated with an ABS HILS system which consist of 17 DOF vehicle model and real ABS hardware parts. The HILS simulation results show that the proposed algorithm may be used for emergency lane-change maneuvers for autonomous vehicles.

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Design of the Optimal Controller for Takagi-Sugeno Fuzzy Systems and Its Application to Spacecraft control (Takagi-Sugeno 퍼지시스템에 대한 최적 제어기 설계 및 우주 비행체의 자세 제어 응용)

  • Park, Yeon-Muk;Tak, Min-Je
    • Journal of Institute of Control, Robotics and Systems
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    • v.7 no.7
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    • pp.589-596
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    • 2001
  • In this paper, a new design methodology for the optimal control of nonlinear systems described by the TS(Takagi-Sugeno) fuzzy model is proposed. First, a new theorem concerning the optimal stabilizing control of a general nonlinear dynamic system is proposed. Next, based on the proposed theorem and the inverse optimal approach, an optimal controller synthesis procedure for a TS fuzzy system is given, Also, it is shown that the optimal controller can be found by solving a linear matrix inequality problem. Finally, the proposed method is applied to the attitude control of a rigid spacecraft to demonstrate its validity.

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Control Bandwidth Extension Method Based on Phase Margin Compensation for Inverters with Low Carrier Ratio

  • Wei, Qikang;Liu, Bangyin;Duan, Shanxu
    • Journal of Power Electronics
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    • v.18 no.6
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    • pp.1760-1770
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    • 2018
  • This paper presents a control bandwidth extension method for inverters with a low carrier ratio. The bandwidth is extended at the price of decreasing the phase margin. Then the phase margin is compensated by introducing an extra leading angle into an inverse Park transformation. The model of the controller with the proposed method is established. The magnitude and phase characteristics are also analyzed. Then the influence on system stability when the leading angle is introduced is analyzed. The proposed method is applied to design an inverter controller with both a large bandwidth and a desired phase margin, and the experimental results verify that the controller performs well in the steady-state and in terms of transient response.

Trajectory control for a Robot Manipulator by using neural network (신경회로망을 사용한 로봇 매니퓰레이터의 궤적 제어)

  • 안덕환;양태규;이상효
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.16 no.7
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    • pp.610-614
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    • 1991
  • This paper proposes a trajectory constrol fo a robot manipulator by using neural network. The inverse dynamic model of manipuator is learned by neural network. The manipulator is controlled by weight values of the learned neural network. The weight valuese is change with a torque of liner vontroller and a acceleration error. Phsically, the totlal torque for a manipualator is a sum of the liner controller torque and the nerural network controller torque. The proposed control effect is estimated by computer simulation.

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Effects of Working Fuel Temperature on Injection Characteristics of Bypass Type Piezo Injector (작동 연료온도가 Bypass type 피에조 인젝터의 분사 특성에 미치는 영향)

  • Cho, Insu;Lee, Jinwook
    • Journal of ILASS-Korea
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    • v.24 no.2
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    • pp.66-72
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    • 2019
  • Diesel vehicles suffer from poor starting and running problems at cold temperatures. Diesel vehicles have the characteristic that CO and PM are reduced or similarly discharged when going from low temperature to high temperature. In this study, a bypass type piezo injector for electronic control based common rail injection system was used. Numerical analysis using injector drive analysis model was performed to analyze injector drive and internal fuel flow characteristics according to fuel temperature change. The results show that the rate of density change due to the fuel temperature is proportional, and that the effect of the kinematic viscosity is relatively large between $-20^{\circ}C$ and $0^{\circ}C$. Comparing the results of temperature condition at $0^{\circ}C$ and $20^{\circ}C$, it is considered that the viscosity is more correlated with the needle displacement than the pressure chamber of the delivery chamber.