• Title/Summary/Keyword: Time Delay Error

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A congestion control scheme estimating global channel busy ratio in VANETs

  • Kim, Tae-won;Jung, Jae-il;Lee, Joo-young
    • Journal of IKEEE
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    • v.21 no.2
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    • pp.115-122
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    • 2017
  • In vehicular safety service, every vehicle broadcasts Basic Safety Message (BSM) periodically to inform neighbor vehicles of host vehicle information. However, this can cause network congestion in a region that is crowded with vehicles resulting in a reduction in the message delivery ratio and an increase in the end-to-end delay. Therefore, it could destabilize the vehicular safety service system. In this paper, in order to improve the congestion control and to consider the hidden node problem, we propose a congestion control scheme using entire network congestion level estimation combined with transmission power control, data rate control and time slot based transmission control algorithm. The performance of this scheme is evaluated using a Qualnet network simulator. The simulation result shows that our scheme mitigates network congestion in heavy traffic cases and enhances network capacity in light traffic cases, so that packet error rate is perfectly within 10% and entire network load level is maintained within 60~70%. Thus, it can be concluded that the proposed congestion control scheme has quite good performance.

Trajectory Control of a Robot Manipulator by TDNN Multilayer Neural Network (TDNN 다층 신경회로망을 사용한 로봇 매니퓰레이터에 대한 궤적 제어)

  • 안덕환;양태규;이상효;유언무
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.5
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    • pp.634-642
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    • 1993
  • In this paper a new trajectory control method is proposed for a robot manipulator using a time delay neural network(TDNN) as a feedforward controller with an algorithm to learn inverse dynamics of the manipulator. The TDNN structure has so favorable characteristics that neurons can extract more dynamic information from both present and past input signals and perform more efficient learning. The TDNN neural network receives two normalized inputs, one of which is the reference trajectory signal and the other of which is the error signals from the PD controller. It is proved that the normalized inputs to the TDNN neural network can enhance the learning efficiency of the neural network. The proposed scheme was investigated for the planar robot manipulator with two joints by computer simulation.

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Hardware-in-the-loop Simulation of CNC-controlled Feed Drives (CNC 제어 이송계의 Hardware-in-the-loop 시뮬레이션)

  • Lee, Wonkyun;Lee, Chan-Young;Kim, Joo-Yeong;Song, Chang Kyu;Min, Byung-Kwon
    • Journal of the Korean Society for Precision Engineering
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    • v.32 no.5
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    • pp.447-454
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    • 2015
  • Design and application of hardware-in-the-loop simulation (HILS) for design of CNC-controlled machine tool feed drives is discussed. The CNC machine tool is a complex mechatronics system where the complexity results from the software-based controller composed of a variety of functionalities and advanced control algorithms. Therefore, using a real CNC controller in the control simulation has merits considering the efforts and accuracy of the simulation modeling. In this paper challenges in HILS for a CNC controlled feed drive, such as minimization of time delay and transmission error that are caused by discretization of the feed drive model, is elaborated. Using an experimental HILS setup of a machine tool feed drive applications in controller gain selection and CNC diagnostics are presented.

Multiobjective PI/PID Control Design Using an Iterative Linear Matrix Inequalities Algorithm

  • Bevrani, Hassan;Hiyama, Takashi
    • International Journal of Control, Automation, and Systems
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    • v.5 no.2
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    • pp.117-127
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    • 2007
  • Many real world control systems usually track several control objectives, simultaneously. At the moment, it is desirable to meet all specified goals using the controllers with simple structures like as proportional-integral (PI) and proportional-integral-derivative (PID) which are very useful in industry applications. Since in practice, these controllers are commonly tuned based on classical or trial-and-error approaches, they are incapable of obtaining good dynamical performance to capture all design objectives and specifications. This paper addresses a new method to bridge the gap between the power of optimal multiobjective control and PI/PID industrial controls. First the PI/PID control problem is reduced to a static output feedback control synthesis through the mixed $H_2/H_{\infty}$ control technique, and then the control parameters are easily carried out using an iterative linear matrix inequalities (ILMI) algorithm. Numerical examples on load-frequency control (LFC) and power system stabilizer (PSS) designs are given to illustrate the proposed methodology. The results are compared with genetic algorithm (GA) based multiobjective control and LMI based full order mixed $H_2/H_{\infty}$ control designs.

A Study on DC Offset Removal using Low-Pass Filter in AT Feeder System for Electric Railway (전기철도 AT급전계통에 Low-Pass Filter를 이용한 직류옵셋 제거에 관한 연구)

  • Lee, Hwan;Jung, No-Geon;Kim, Jae-Moon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.65 no.6
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    • pp.1108-1114
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    • 2016
  • The cause of failure in the AT feeding system is divided into grounding, short-circuit of feeding circuit and internal faults of the railway substation. Since the fault current is very high, real-time current is detected and the failure must be immediately removed. In this paper, a new DC offset elimination filter that can remove component to decrease in the form of exponential function using low-pass filter was proposed in order to extract the fundamental wave from distorted fault current. In order to confirm the performance of the proposed filter method, AT feeder system was modelled by simulation tool and simulations were performed under various conditions such as fault location, fault resistance and fault voltage phase angle in case of trolley-rail short-circuit fault. When applying the proposed DC-offset removal method, it can be seen that the phase delay and gain error did not appear.

Analysis and Application of Repetitive Control Scheme for Three-Phase Active Power Filter with Frequency Adaptive Capability

  • Sun, Biaoguang;Xie, Yunxiang;Ma, Hui;Cheng, Li
    • Journal of Electrical Engineering and Technology
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    • v.11 no.3
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    • pp.618-628
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    • 2016
  • Active power filter (APF) has been proved as a flexible solution for compensating the harmonic distortion caused by nonlinear loads in power distribution power systems. Digital repetitive control can achieve zero steady-state error tracking of any periodic signal while the sampling points within one repetitive cycle must be a known integer. However, the compensation performance of the APF would be degradation when the grid frequency varies. In this paper, an improved repetitive control scheme with frequency adaptive capability is presented to track any periodic signal with variable grid frequency, where the variable delay items caused by time-varying grid frequency are approximated with Pade approximants. Additionally, the stability criterion of proposed repetitive control scheme is given. A three-phase shunt APF experimental platform with proposed repetitive control scheme is built in our laboratory. Simulation and experimental results demonstrate the effectiveness of the proposed repetitive control scheme.

Single Channel Active Noise Control using Adaptive Model (적응모델을 이용한 단일채널 능동 소음제어)

  • Kim, Yeong-Dal;Lee, Min-Myeong;Jeong, Chang-Gyeong
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.8
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    • pp.442-450
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    • 2000
  • Active noise control is an approach to noise reduction in which a secondary noise source that destructively interferes with the unwanted noise. In general, active noise control systems rely on multiple sensors to measure the unwanted noise field and the effect of the cancellation. This paper develops an approach that utilizes a single sensor. The noise field is modeled as a stochastic process, and a time-adaptive algorithm is used to adaptively estimate the parameters of the process. Based on these parameter estimates, a canceling signal is generated. Opppenheim model assumed that transfer function characteristics from the canceling source to the error sensor is only propagation delay. But this paper proposes a modified Oppenheim model by considering transfer characteristics of acoustic device and noise path. This transfer characteristics is adaptively cancelled by adaptive model. This is proved by computer simulation with artifically generated random noise and sine wave noise. The details of the proposed architecture, and theoretical simulation and experimental results of the noise cancellation system for three dimension enclosure are presented in the paper.

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Digit-Parallel/Bit-Serial Multiplier for GF$(2^m)$ Using Polynomial Basis (다항식기저를 이용한 GF$(2^m)$ 상의 디지트병렬/비트직렬 곱셈기)

  • Cho, Yong-Suk
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.11C
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    • pp.892-897
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    • 2008
  • In this paper, a new architecture for digit-parallel/bit-serial GF$(2^m)$ multiplier with low latency is proposed. The proposed multiplier operates in polynomial basis of GF$(2^m)$ and produces multiplication results at a rate of one per D clock cycles, where D is the selected digit size. The digit-parallel/bit-serial multiplier is faster than bit-serial ones but with lower area complexity than bit-parallel ones. The most significant feature of the proposed architecture is that a trade-off between hardware complexity and delay time can be achieved.

Vehicle Steering System Analysis for Enhanced Path Tracking of Autonomous Vehicles (자율주행 경로 추종 성능 개선을 위한 차량 조향 시스템 특성 분석)

  • Kim, Changhee;Lee, Dongpil;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.12 no.2
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    • pp.27-32
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    • 2020
  • This paper presents steering system requirements to ensure the stabilized lateral control of autonomous driving vehicles. The two main objectives of a lateral controller in autonomous vehicles are maintenance of vehicle stability and tracking of the desired path. Even if the desired steering angle is immediately determined by the upper level controller, the overall controller performance is greatly influenced by the specification of steering system actuators. Since one of the major inescapable traits that affects controller performance is the time delay of the steering actuator, our work is mainly focused on finding adequate parameters of high level control algorithm to compensate these response characteristics and guarantee vehicle stability. Actual vehicle steering angle response was obtained with Electric Power Steering (EPS) actuator test subject to various longitudinal velocity. Steering input and output response analysis was performed via MATLAB system identification toolbox. The use of system identification is advantageous since the transfer function of the system is conveniently obtained compared with methods that require actual mathematical modeling of the system. Simulation results of full vehicle model suggest that the obtained tuning parameter yields reduced oscillation and lateral error compared with other cases, thus enhancing path tracking performance.

TDOA Based Moving Target Velocity Estimation in Sensor Network (센서네트워크 내에서 TDOA 측정치 기반의 이동 표적 속도 정보 추정)

  • Kim, Yong Hwi;Park, Min Soo;Park, Jin Bae;Yoon, Tae Sung
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.64 no.3
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    • pp.445-450
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    • 2015
  • In the moving target problem, the velocity information of the moving target is very important as well as the high accuracy position information. To solve this problem, active researches are being conducted recently with combine the Time Difference of Arrival (TDOA) and Frequency Delay of Arrival(FDOA) measurements. However, since the FDOA measurement is utilizing the Doppler effect due to the relative velocity between the target source and the receiver sensor, it may be difficult to use the FDOA measurement if the moving target speed is not sufficiently fast. In this paper, we propose a method for estimating the position and the velocities of the target by using only the TDOA measurements for the low speed moving target in the indoor environment with sensor network. First, the target position and heading angle are obtained from the estimated positions of two attached transmitters on the target. Then, the target angular and linear velocities are also estimated. In addtion, we apply the Instrumental Variable (IV) technique to compensate the estimation error of the estimated target velocity. In simulation, the performance of the proposed algorithm is verified.