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Complexity Estimation Based Work Load Balancing for a Parallel Lidar Waveform Decomposition Algorithm

  • Jung, Jin-Ha;Crawford, Melba M.;Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.25 no.6
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    • pp.547-557
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    • 2009
  • LIDAR (LIght Detection And Ranging) is an active remote sensing technology which provides 3D coordinates of the Earth's surface by performing range measurements from the sensor. Early small footprint LIDAR systems recorded multiple discrete returns from the back-scattered energy. Recent advances in LIDAR hardware now make it possible to record full digital waveforms of the returned energy. LIDAR waveform decomposition involves separating the return waveform into a mixture of components which are then used to characterize the original data. The most common statistical mixture model used for this process is the Gaussian mixture. Waveform decomposition plays an important role in LIDAR waveform processing, since the resulting components are expected to represent reflection surfaces within waveform footprints. Hence the decomposition results ultimately affect the interpretation of LIDAR waveform data. Computational requirements in the waveform decomposition process result from two factors; (1) estimation of the number of components in a mixture and the resulting parameter estimates, which are inter-related and cannot be solved separately, and (2) parameter optimization does not have a closed form solution, and thus needs to be solved iteratively. The current state-of-the-art airborne LIDAR system acquires more than 50,000 waveforms per second, so decomposing the enormous number of waveforms is challenging using traditional single processor architecture. To tackle this issue, four parallel LIDAR waveform decomposition algorithms with different work load balancing schemes - (1) no weighting, (2) a decomposition results-based linear weighting, (3) a decomposition results-based squared weighting, and (4) a decomposition time-based linear weighting - were developed and tested with varying number of processors (8-256). The results were compared in terms of efficiency. Overall, the decomposition time-based linear weighting work load balancing approach yielded the best performance among four approaches.

Experimental Evaluation of Levitation and Imbalance Compensation for the Magnetic Bearing System Using Discrete Time Q-Parameterization Control (이산시간 Q 매개변수화 제어를 이용한 자기축수 시스템에 대한 부상과 불평형보정의 실험적 평가)

  • ;Fumio Matsumura
    • Journal of KSNVE
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    • v.8 no.5
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    • pp.964-973
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    • 1998
  • In this paper we propose a levitation and imbalance compensation controller design methodology of magnetic bearing system. In order to achieve levitation and elimination of unbalance vibartion in some operation speed we use the discrete-time Q-parameterization control. When rotor speed p = 0 there are no rotor unbalance, with frequency equals to the rotational speed. So in order to make levitatiom we choose the Q-parameterization controller free parameter Q such that the controller has poles on the unit circle at z = 1. However, when rotor speed p 0 there exist sinusoidal disturbance forces, with frequency equals to the rotational speed. So in order to achieve asymptotic rejection of these disturbance forces, the Q-parameterization controller free parameter Q is chosen such that the controller has poles on the unit circle at z = expipTs for a certain speed of rotation p ( Ts is the sampling period). First, we introduce the experimental setup employed in this research. Second, we give a mathematical model for the magnetic bearing in difference equation form. Third, we explain the proposed discrete-time Q-parameterization controller design methodology. The controller free parameter Q is assumed to be a proper stable transfer function. Fourth, we show that the controller free parameter which satisfies the design objectives can be obtained by simply solving a set of linear equations rather than solving a complicated optimization problem. Finally, several simulation and experimental results are obtained to evaluate the proposed controller. The results obtained show the effectiveness of the proposed controller in eliminating the unbalance vibrations at the design speed of rotation.

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Stability Analysis of a Networked Control System with Multiple Packet Transmission (다중 패킷을 전송하는 네트워크 제어시스템의 안정성 분석)

  • Jung, Joon-Hong;Park, Ki-Heon;Lee, Jae-Ho
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.44 no.5
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    • pp.18-29
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    • 2007
  • The main objective of this paper is to propose a new stability analysis method for a networked control system with multiple packet transmission. The new scheduling method that can guarantee the maximum time delay and discrete switch state equation model which represent a network data loss is proposed. The equivalent model of a MIMO(multi-input multi-output) networked control system is derived from a state space model of linear time invariant interconnected systems in the form of asynchronous dynamical system. Using this model, this paper presents new stability theorems that can determine stability of the networked control system with regard to time delay, data loss, and the number of transmission packets. Simulation results verify the effectiveness of proposed stability analysis method.

Intelligent Digital Redesign of Biodynamic Model of HIV-1 (HIV-1 바이오 동역학 모델의 지능형 디지털 재설계)

  • Kim Do-Wan;Joo Young-Hoon;Park Jin-Bae
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.6
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    • pp.547-553
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    • 2006
  • This paper studies digital control of biodynamic model of HIV-1 via intelligent digital redesign (IDR). The purpose of the IDR is to develop an equivalent digital fuzzy controller maintaining the satisfactory performance of an existing continuous-time fuzzy controller in the sense of the state-matching. Some conditions for the stability as well as the global state-matching are provided.. They are given by the form of the linear matrix inequalities (LMIs) and thereby easily tractable by the convex optimization techniques. The main features of the proposed method are that 1) the generalized control scheme is provided for the multirate as well as the single-rate digital controllers; 2) a new compensated block-pulse function method is applied to closely match the states of the continuous-time and the sampled-data fuzzy systems in the discrete-time domain; 3) the two-step procedure of IDR is presented to prevent the performance degradation caused by the additional stability conditions. The applicability of the proposed approach is shown through the biodynamic model of HIV-1.

A Study on the Underwater Navigation System with Adaptive Receding Horizon Kalman Filter (적응 이동 구간 칼만 필터를 이용한 무인 잠수정의 항법 시스템에 관한 연구)

  • Jo, Gyung-Nam;Seo, Dong-C.;Choi, Hang-S.
    • Journal of the Society of Naval Architects of Korea
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    • v.45 no.3
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    • pp.269-279
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    • 2008
  • In this paper, an underwater navigation system with adaptive receding horizon Kalman filter (ARHKF) is studied. It is well known that incorrect statistical information and temporal disturbance invoke errors of any navigation systems with Kalman filter, which makes the autonomous navigation difficult in real underwater environment. In this context, two kinds of problems are herein considered. The first one is the development of an algorithm, which estimates the noise covariance of a linear discrete time-varying stochastic system. The second one is the implementation of ARHKF to underwater navigation systems. The performance of the derived estimation algorithm of noise covariance and the ARHKF are verified by simulation and experiment in the towing tank of Seoul National University.

On discrete nonlinear self-tuning control

  • Mohler, R.-R.;Rajkumar, V.;Zakrzewski, R.-R.
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10b
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    • pp.1659-1663
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    • 1991
  • A new control design methodology is presented here which is based on a nonlinear time-series reference model. It is indicated by highly nonlinear simulations that such designs successfully stabilize troublesome aircraft maneuvers undergoing large changes in angle of attack as well as large electric power transients due to line faults. In both applications, the nonlinear controller was significantly better than the corresponding linear adaptive controller. For the electric power network, a flexible a.c. transmission system (FACTS) with series capacitor power feedback control is studied. A bilinear auto-regressive moving average (BARMA) reference model is identified from system data and the feedback control manipulated according to a desired reference state. The control is optimized according to a predictive one-step quadratic performance index (J). A similar algorithm is derived for control of rapid changes in aircraft angle of attack over a normally unstable flight regime. In the latter case, however, a generalization of a bilinear time-series model reference includes quadratic and cubic terms in angle of attack. These applications are typical of the numerous plants for which nonlinear adaptive control has the potential to provide significant performance improvements. For aircraft control, significant maneuverability gains can provide safer transportation under large windshear disturbances as well as tactical advantages. For FACTS, there is the potential for significant increase in admissible electric power transmission over available transmission lines along with energy conservation. Electric power systems are inherently nonlinear for significant transient variations from synchronism such as may result for large fault disturbances. In such cases, traditional linear controllers may not stabilize the swing (in rotor angle) without inefficient energy wasting strategies to shed loads, etc. Fortunately, the advent of power electronics (e.g., high-speed thyristors) admits the possibility of adaptive control by means of FACTS. Line admittance manipulation seems to be an effective means to achieve stabilization and high efficiency for such FACTS. This results in parametric (or multiplicative) control of a highly nonlinear plant.

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Real-time Fault Detection System of a Pneumatic Cylinder Via Deep-learning Model Considering Time-variant Characteristic of Sensor Data (센서 데이터의 시계열 특성을 고려한 딥러닝 모델 기반의 공압 실린더 고장 감지 시스템 구현)

  • Byeong Su Kim;Geun Myeong Song;Min Jeong Lee;Sujeong Baek
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.47 no.2
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    • pp.10-20
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    • 2024
  • In recent automated manufacturing systems, compressed air-based pneumatic cylinders have been widely used for basic perpetration including picking up and moving a target object. They are relatively categorized as small machines, but many linear or rotary cylinders play an important role in discrete manufacturing systems. Therefore, sudden operation stop or interruption due to a fault occurrence in pneumatic cylinders leads to a decrease in repair costs and production and even threatens the safety of workers. In this regard, this study proposed a fault detection technique by developing a time-variant deep learning model from multivariate sensor data analysis for estimating a current health state as four levels. In addition, it aims to establish a real-time fault detection system that allows workers to immediately identify and manage the cylinder's status in either an actual shop floor or a remote management situation. To validate and verify the performance of the proposed system, we collected multivariate sensor signals from a rotary cylinder and it was successful in detecting the health state of the pneumatic cylinder with four severity levels. Furthermore, the optimal sensor location and signal type were analyzed through statistical inferences.

Improvement of inspection system for common crossings by track side monitoring and prognostics

  • Sysyn, Mykola;Nabochenko, Olga;Kovalchuk, Vitalii;Gruen, Dimitri;Pentsak, Andriy
    • Structural Monitoring and Maintenance
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    • v.6 no.3
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    • pp.219-235
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    • 2019
  • Scheduled inspections of common crossings are one of the main cost drivers of railway maintenance. Prognostics and health management (PHM) approach and modern monitoring means offer many possibilities in the optimization of inspections and maintenance. The present paper deals with data driven prognosis of the common crossing remaining useful life (RUL) that is based on an inertial monitoring system. The problem of scheduled inspections system for common crossings is outlined and analysed. The proposed analysis of inertial signals with the maximal overlap discrete wavelet packet transform (MODWPT) and Shannon entropy (SE) estimates enable to extract the spectral features. The relevant features for the acceleration components are selected with application of Lasso (Least absolute shrinkage and selection operator) regularization. The features are fused with time domain information about the longitudinal position of wheels impact and train velocities by multivariate regression. The fused structural health (SH) indicator has a significant correlation to the lifetime of crossing. The RUL prognosis is performed on the linear degradation stochastic model with recursive Bayesian update. Prognosis testing metrics show the promising results for common crossing inspection scheduling improvement.

Performance Evaluation of Channel Estimation Scheme for ATSC 3.0 MIMO under Fixed Reception Environment (고정 수신 환경에서 ATSC 3.0 MIMO의 채널 추정 방법에 따른 성능 평가)

  • Kim, Hyeongseok;Yeom, Myeonggil;Kim, Jeongchang;Park, Sung-Ik;Jung, Hoiyoon;Hur, Namho
    • Journal of Broadcast Engineering
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    • v.24 no.5
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    • pp.879-891
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    • 2019
  • This paper provides performance evaluations of various channel estimation schemes for Advanced Television Systems Committee (ATSC) 3.0 multiple-input multiple-output (MIMO) system under a fixed reception environment. ATSC 3.0 MIMO system can obtain high spectral efficiency and improved reception performance compared to conventional terrestrial broadcasting systems. The ATSC 3.0 MIMO defines Walsh-Hadamard and null pilot encoding algorithms and the amplitude and phase of MIMO pilots are different from those of single-input single-output pilots. At the receiver, linear and discrete Fourier transform (DFT)-based interpolations can be used for the channel estimation. This paper provides the various combinations of the interpolation schemes for channel estimation in time and frequency dimensions, and then analyzes the performance of the various combinations through the computer simulation. The results of computer simulation show that the combination of the linear interpolation in the time dimension and then DFT-based interpolation in the frequency dimension can obtain the best performance among the considered combinations.

A Globally Stabilizing Model Predictive Controller for Neutrally Stable Linear Systems with Input Constraints

  • Yoon, Tae-Woong;Kim, Jung-Su;Jadbabaie, Ali;Persis, Claudio De
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1901-1904
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    • 2003
  • MPC or model predictive control is representative of control methods which are able to handle physical constraints. Closed-loop stability can therefore be ensured only locally in the presence of constraints of this type. However, if the system is neutrally stable, and if the constraints are imposed only on the input, global aymptotic stability can be obtained; until recently, use of infinite horizons was thought to be inevitable in this case. A globally stabilizing finite-horizon MPC has lately been suggested for neutrally stable continuous-time systems using a non-quadratic terminal cost which consists of cubic as well as quadratic functions of the state. The idea originates from the so-called small gain control, where the global stability is proven using a non-quadratic Lyapunov function. The newly developed finite-horizon MPC employs the same form of Lyapunov function as the terminal cost, thereby leading to global asymptotic stability. A discrete-time version of this finite-horizon MPC is presented here. The proposed MPC algorithm is also coded using an SQP (Sequential Quadratic Programming) algorithm, and simulation results are given to show the effectiveness of the method.

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