• 제목/요약/키워드: Motion predictive control

검색결과 35건 처리시간 0.02초

신경회로망 예측 PID 제어법을 이용한 컨테이너 크레인의 자동주행제어 (An Automatic Travel Control of a Container Crane using Neural Network Predictive PID Control Technique)

  • 서진호;이진우;이영진;이권순
    • 한국정밀공학회지
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    • 제22권1호
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    • pp.61-72
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    • 2005
  • In this paper, we develop anti-sway control in proposed techniques for an ATC system. The developed algorithm is to build the optimal path of container motion and to calculate an anti-collision path for collision avoidance in its movement to the finial coordinate. Moreover, in order to show the effectiveness in this research, we compared NNP PID controller to be tuning parameters of controller using NN with 2 DOF PID controller. The experimental results for an ATC simulator show that the proposed control scheme guarantees performances, trolley position, sway angle, and settling time in NNP PID controller than other controller. As a result, the application of NNP PID controller is analyzed to have robustness about disturbance which is wind of fixed pattern in the yard. Accordingly, the proposed algorithm in this study can be readily used for industrial applications

Prediction of Motion State of a Docking Small Planing Ship using Artificial Neural Network

  • Hoang Thien Vu;Thi Thanh Diep Nguyen;Hyeon Kyu Yoon
    • 한국항해항만학회지
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    • 제48권2호
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    • pp.116-124
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    • 2024
  • Automatic docking of small planing ship is a critical aspect of maritime operations, requiring accurate prediction of motion states to ensure safe and efficient maneuvers. This study investigates the use of Artificial Neural Network (ANN) to predict motion state of a small planing ship to enhance navigation automation in port environments. To achieve this, simulation tests were conducted to control a small planing ship while docking at various heading angles in calm water and in waves. Comprehensive analysis of the ANN-based predictive model was conducted by training and validation using data from various docking situations to improve its ability to accurately capture motion characteristics of a small planing ship. The trained ANN model was used to predict the motion state of the small planning ship based on any initial motion state. Results showed that the small planing ship could dock smoothly in both calm water and waves conditions, confirming the accuracy and reliability of the proposed method for prediction. Moreover, the ANN-based prediction model can adjust the dynamic model of the small planing ship to adapt in real-time and enhance the robustness of an automatic positioning system. This study contributes to the ongoing development of automated navigation systems and facilitates safer and more efficient maritime transport operations.

자율주행 차량의 다 차선 환경 내 차량 추종 경로 계획 (Car-following Motion Planning for Autonomous Vehicles in Multi-lane Environments)

  • 서장필;이경수
    • 자동차안전학회지
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    • 제11권3호
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    • pp.30-36
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    • 2019
  • This paper suggests a car-following algorithm for urban environment, with multiple target candidates. Until now, advanced driver assistant systems (ADASs) and self-driving technologies have been researched to cope with diverse possible scenarios. Among them, car-following driving has been formed the groundwork of autonomous vehicle for its integrity and flexibility to other modes such as smart cruise system (SCC) and platooning. Although the field has a rich history, most researches has been focused on the shape of target trajectory, such as the order of interpolated polynomial, in simple single-lane situation. However, to introduce the car-following mode in urban environment, realistic situation should be reflected: multi-lane road, target's unstable driving tendency, obstacles. Therefore, the suggested car-following system includes both in-lane preceding vehicle and other factors such as side-lane targets. The algorithm is comprised of three parts: path candidate generation and optimal trajectory selection. In the first part, initial guesses of desired paths are calculated as polynomial function connecting host vehicle's state and vicinal vehicle's predicted future states. In the second part, final target trajectory is selected using quadratic cost function reflecting safeness, control input efficiency, and initial objective such as velocity. Finally, adjusted path and control input are calculated using model predictive control (MPC). The suggested algorithm's performance is verified using off-line simulation using Matlab; the results shows reasonable car-following motion planning.

초정밀 자기부상 스테이지용 능동진동제어시스템 설계 (A Design Of Active Vibration Control System For Precise Maglev Stage)

  • 이주훈;김용주;손성완;이홍기;이세한;최영규
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2004년도 추계학술대회논문집
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    • pp.121-124
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    • 2004
  • In this paper, we address an active vibration control system, which suppresses the vibration engaged by magnetically levitated stage. The stage system consists of a levitating platen with four permanent magnetic linear synchronous motors in parallel. Each motor generates vertical force fer suspension against gravity and propulsion force horizontally as well. This stage can generate six degrees of freedom motion via the vertical and horizontal forces. In the stage system, which represents the settling-time critical system. the motion of the platen vibrates mechanically. We designed an active vibration control system for suppressing vibration due to the stage moving. The command feedforward with inertial feedback algorithm is used fer solving stage system's critical problems. The components of the active vibration control system are accelerometers for detecting stage table's vibrations, a digital controller with high precise signal converters, and electromagnetic actuators.

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자율주행 버스의 주행 안전을 위한 차량 간 통신 및 모델 예측 제어 기반 종 방향 거동 계획 (Proactive Longitudinal Motion Planning for Improving Safety of Automated Bus using Chance-constrained MPC with V2V Communication)

  • 조아라;유진수;곽지섭;권우진;이경수
    • 자동차안전학회지
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    • 제15권4호
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    • pp.16-22
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    • 2023
  • This paper presents a proactive longitudinal motion planning algorithm for improving the safety of an automated bus. Since the field of view (FOV) of the autonomous vehicle was limited depending on onboard sensors' performance and surrounding environments, it was necessary to implement vehicle-to-vehicle (V2V) communication for overcoming the limitation. After a virtual V2V-equipped target was constructed considering information obtained from V2V communication, the reference motion of the ego vehicle was determined by considering the state of both the V2V-equipped target and the sensor-detected target. Model predictive control (MPC) was implemented to calculate the optimal motion considering the reference motion and the chance constraint, which was deduced from manual driving data. The improvement in driving safety was confirmed through vehicle tests along actual urban roads.

Optimal deep machine learning framework for vibration mitigation of seismically-excited uncertain building structures

  • Afshin Bahrami Rad;Javad Katebi;Saman Yaghmaei-Sabegh
    • Structural Engineering and Mechanics
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    • 제88권6호
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    • pp.535-549
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    • 2023
  • Deep extreme learning machine (DELM) and multi-verse optimization algorithms (MVO) are hybridized for designing an optimal and adaptive control framework for uncertain buildings. In this approach, first, a robust model predictive control (RMPC) scheme is developed to handle the problem uncertainty. The optimality and adaptivity of the proposed controller are provided by the optimal determination of the tunning weights of the linear programming (LP) cost function for clustered external loads using the MVO. The final control policy is achieved by collecting the clustered data and training them by DELM. The efficiency of the introduced control scheme is demonstrated by the numerical simulation of a ten-story benchmark building subjected to earthquake excitations. The results represent the capability of the proposed framework compared to robust MPC (RMPC), conventional MPC (CMPC), and conventional DELM algorithms in structural motion control.

지능형 예측감시 시스템을 위한 보안 프레임워크 (Security Framework for Intelligent Predictive Surveillance Systems)

  • 박정훈;박남제
    • 한국융합학회논문지
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    • 제11권3호
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    • pp.77-83
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    • 2020
  • 최근 지능형 예측감시 시스템이 등장하고 있다. 지능형 예측감시 시스템의 추론을 위해서는 현재 및 과거의 데이터가 필요하며, 이러한 데이터의 분석을 통하여 곧 발생할 상황에 대한 예측을 가능하게 한다. 그러나, 이러한 과정에서 영상 객체의 개인정보를 취급하게 될 소지가 높으므로, 개인정보보호를 위해서는 보안에 대한 고려가 필수적이다. 특히, 개인의 생활패턴, 주요 이동 경로 등에 대한 정보가 해킹을 통하여 공개적으로 노출된다면 프라이버시 측면에서 문제가 될 것이다. 기존의 영상감시 프레임워크는 개인정보보호 측면에서 한계점이 있으며, 특히 개인정보보호에 취약한 측면이 있다. 본 논문에서는 개인정보보호를 고려한 지능형 예측감시 시스템을 위한 보안 프레임워크를 제안하였다. 제안한 방법에서는 단말, 전송, 감시, 모니터링 계층으로 구분하여 단위별 세부 구성요소를 명시하였으며, 특히 객체 단위별 세부 접근제어와 비식별화를 지원하여 영상감시 과정에서의 능동형 개인정보보호가 가능하다. 또한, 데이터 전송시 보안 기능과 RBAC 제공을 통한 접근제어의 장점을 갖는다.

엔트로피 코딩 기반의 분산 비디오 코딩을 위한 블록 기반 복잡도 분배 (Complexity Balancing for Distributed Video Coding Based on Entropy Coding)

  • 유성은;민경연;심동규
    • 방송공학회논문지
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    • 제16권1호
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    • pp.133-143
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    • 2011
  • 본 논문은 엔트로피 코딩 기반 분산 비디오 코딩 시스템에서의 복잡도 분배 기법을 제안한다. 제안하는 방법은 복호화기의 복잡도 감소를 위하여 채널 코더 대신 엔트로피 코더를 이용하며, 저 복잡도로 높은 부호화 효율을 얻기 위한 블록 단위 복잡도 분배 방법을 수행한다. 제안하는 분산 비디오 복호화기는 움직임 추정을 수행하여 측정된 움직임 벡터를 부호화기로 전송하고, 부호화기에서는 복호화기로부터 수신된 움직임 벡터를 보정하여 보다 정확한 움직임 추정을 수행한다. 움직임 벡터의 보정을 수행 시, 수신된 움직임 벡터와 예측 움직임 벡터를 이용하여 최적의 예측 움직임 벡터를 결정하며, 움직임 벡터와 예측 움직임 벡터의 차에 따라 범위를 조절함으로써 블록의 복잡도를 적응적으로 할당한다. 제안하는 부호화기는 H.264/AVC의 부호화기의 복잡도에 비교하여 11.8% 감소하였고, 제안하는 복호화기는 기존의 분산 비디오 시스템의 복호화기 복잡도보다 99%감소되다.

Human Postural Dynamics in Response to the Horizontal Vibration

  • Shin Young-Kyun;Fard Mohammad A.;Inooka Hikaru;Kim Il-Hwan
    • International Journal of Control, Automation, and Systems
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    • 제4권3호
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    • pp.325-332
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    • 2006
  • The dynamic responses of human standing postural control were investigated when subjects were exposed to long-term horizontal vibration. It was hypothesized that the motion of standing posture complexity mainly occurs in the mid-sagittal plane. The motor-driven support platform was designed as a source of vibration. The AC Servo-controlled motors produced anterior/posterior (AP) motion. The platform acceleration and the trunk angular velocity were used as the input and the output of the system, respectively. A method was proposed to identify the complexity of the standing posture dynamics. That is, during AP platform motion, the subject's knee, hip and neck were tightly constrained by fixing assembly, so the lower extremity, trunk and head of the subject's body were individually immovable. Through this method, it was assumed that the ankle joint rotation mainly contributed to maintaining their body balance. Four subjects took part in this study. During the experiment, the random vibration was generated at a magnitude of $0.44m/s^2$, and the duration of each trial was 40 seconds. Measured data were estimated by the coherence function and the frequency response function for analyzing the dynamic behavior of standing control over a frequency range from 0.2 to 3 Hz. Significant coherence values were found above 0.5 Hz. The estimation of frequency response function revealed the dominant resonance frequencies between 0.60 Hz and 0.68 Hz. On the basis of our results illustrated here, the linear model of standing postural control was further concluded.

Neck Pain in Adults with Forward Head Posture: Effects of Craniovertebral Angle and Cervical Range of Motion

  • Kim, Dae-Hyun;Kim, Chang-Ju;Son, Sung-Min
    • Osong Public Health and Research Perspectives
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    • 제9권6호
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    • pp.309-313
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    • 2018
  • Objectives: The purpose of this study was to determine whether the cranial vertebral angle (CVA) and the range of motion (ROM) was different between participants with a forward head posture (FHP), with or without pain. Methods: Forty-four participants who had FHP participated in this study. The FHP was assessed digitally by measuring a lateral view the CVA for each subject. A cervical ROM device measured the cervical ROM. The volunteers were allocated to either, with pain (n = 22), or without pain (n = 22) groups, and pain was evaluated using the Numeric Pain Rating Scale. Results: The FHP in the pain group showed a significant difference in the CVA, and the cervical ROM in both flexion and extension, compared with those in the FHP without pain group (p < 0.05). Logistic regression analysis indicated that the occurrence of cervical area pain was higher amongst subjects who had a decreased CVA and flexion motion. Conclusion: This study suggested that decreased CVA and cervical flexion range, were predictive factors for the occurrence of pain in the cervical region.