• Title/Summary/Keyword: automation technology

Search Result 2,417, Processing Time 0.027 seconds

Delay-Dependent Guaranteed Cost Control for Uncertain Neutral Systems with Distributed Delays

  • Li, Yongmin;Xu, Shengyuan;Zhang, Baoyong;Chu, Yuming
    • International Journal of Control, Automation, and Systems
    • /
    • v.6 no.1
    • /
    • pp.15-23
    • /
    • 2008
  • This paper considers the problem of delay-dependent guaranteed cost controller design for uncertain neutral systems with distributed delays. The system under consideration is subject to norm-bounded time-varying parametric uncertainty appearing in all the matrices of the state-space model. By constructing appropriate Lyapunov functionals and using matrix inequality techniques, a state feedback controller is designed such that the resulting closed-loop system is not only robustly stable but also guarantees an adequate level of performance for all admissible uncertainties. Furthermore, a convex optimization problem is introduced to minimize a specified cost bound. By matrix transformation techniques, the corresponding optimal guaranteed controller can be obtained by solving a linear matrix inequality. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed approach.

DETECTION AND RESTORATION OF NON-RADIAL VARIATION OVER FULL-DISK SOLAR IMAGES

  • Yang, Yunfei;Lin, Jiaben;Feng, Song;Deng, Hui;Wang, Feng;Ji, Kaifan
    • Journal of The Korean Astronomical Society
    • /
    • v.46 no.5
    • /
    • pp.191-200
    • /
    • 2013
  • Full-disk solar images are provided by many solar telescopes around the world. However, the observed images show Non-Radial Variation (NRV) over the disk. In this paper, we propose algorithms for detecting distortions and restoring these images. For detecting NRV, the cross-correlation coefficients matrix of radial profiles is calculated and the minimum value in the matrix is defined as the Index of Non-radial Variation (INV). This index has been utilized to evaluate the H images of GONG, and systemic variations of different instruments are obtained. For obtaining the NRV's image, a Multi-level Morphological Filter (MMF) is designed to eliminate structures produced by solar activities over the solar surface. Comparing with the median filter, the proposed filter is a better choice. The experimental results show that the effect of our automatic detection and restoration methods is significant for getting a flat and high contrast full-disk image. For investigating the effect of our method on solar features, structural similarity (SSIM) index is utilized. The high SSIM indices (close to 1) of solar features show that the details of the structures remain after NRV restoring.

AUTOMATIC DETECTION AND EXTRACTION ALGORITHM OF INTER-GRANULAR BRIGHT POINTS

  • Feng, Song;Ji, Kai-Fan;Deng, Hui;Wang, Feng;Fu, Xiao-Dong
    • Journal of The Korean Astronomical Society
    • /
    • v.45 no.6
    • /
    • pp.167-173
    • /
    • 2012
  • Inter-granular Bright Points (igBPs) are small-scale objects in the Solar photosphere which can be seen within dark inter-granular lanes. We present a new algorithm to automatically detect and extract igBPs. Laplacian and Morphological Dilation (LMD) technique is employed by the algorithm. It involves three basic processing steps: (1) obtaining candidate "seed" regions by Laplacian; (2) determining the boundary and size of igBPs by morphological dilation; (3) discarding brighter granules by a probability criterion. For validating our algorithm, we used the observed samples of the Dutch Open Telescope (DOT), collected on April 12, 2007. They contain 180 high-resolution images, and each has a $85{\times}68\;arcsec^2$ field of view (FOV). Two important results are obtained: first, the identified rate of igBPs reaches 95% and is higher than previous results; second, the diameter distribution is $220{\pm}25km$, which is fully consistent with previously published data. We conclude that the presented algorithm can detect and extract igBPs automatically and effectively.

EMI Noise Source Reduction of Single-Ended Isolated Converters Using Secondary Resonance Technique

  • Chen, Zhangyong;Chen, Yong;Chen, Qiang;Jiang, Wei;Zhong, Rongqiang
    • Journal of Power Electronics
    • /
    • v.19 no.2
    • /
    • pp.403-412
    • /
    • 2019
  • Aiming at the problems of large dv/dt and di/dt in traditional single-ended converters and high electromagnetic interference (EMI) noise levels, a single-ended isolated converter using the secondary resonance technique is proposed in this paper. In the proposed converter, the voltage stress of the main power switch can be reduced and the voltage across the output diode is clamped to the output voltage when compared to the conventional flyback converter. In addition, the peak current stress through the main power switch can be decreased and zero current switching (ZCS) of the output diode can be achieved through the resonance technique. Moreover, the EMI noise coupling path and an equivalent model of the proposed converter topology are presented through the operational principle of the proposed converter. Analysis results indicate that the common mode (CM) EMI noise and the differential mode (DM) EMI noise of such a converter are deduced since the frequency spectra of the equivalent controlled voltage sources and controlled current source are decreased when compared with the traditional flyback converter. Furthermore, appropriate parameter selection of the resonant circuit network can increase the equivalent impedance in the EMI coupling path in the low frequency range, which further reduces the common mode interference. Finally, a simulation model and a 60W experimental prototype of the proposed converter are built and tested. Experimental results verify the theoretical analysis.

Repetitive Control with Specific Harmonic Gain Compensation for Cascaded Inverters under Rectifier Loads

  • Lv, Zheng-Kai;Sun, Li;Duan, Jian-Dong;Tian, Bing;Qin, HuiLing
    • Journal of Power Electronics
    • /
    • v.18 no.6
    • /
    • pp.1670-1682
    • /
    • 2018
  • The further improvement of submarine propulsion is associated with the modularity of accumulator-fed inverters, such as cascaded inverters (CIs). CI technology guarantees smooth output voltages with reduced switch frequencies under linear loads. However, the output voltages of CIs are distorted under rectifier loads. This distortion requires harmonic suppression technology. One such technology is the repetitive controller (RC), which is commonly applied but suffers from poor performance in propulsion systems. In this study, the FFT spectrum of a CI under rectifier load is analyzed, and the harmonic contents are uneven in magnitude. For the purpose of harmonic suppression, the control gains at each harmonic frequency should be seriously considered. A RC with a specific harmonic gain compensation (SHGC) for CIs is proposed. This method provides additional control gains at low-order harmonic frequencies, which are difficult to achieve with conventional RCs. This SHGC consists of a band-pass filter (BPF) and proportional element and is easy to implement. These features make the proposed method suitable for submarine propulsion. Experimental results verify the feasibility of the improved RC.

Refined identification of hybrid traffic in DNS tunnels based on regression analysis

  • Bai, Huiwen;Liu, Guangjie;Zhai, Jiangtao;Liu, Weiwei;Ji, Xiaopeng;Yang, Luhui;Dai, Yuewei
    • ETRI Journal
    • /
    • v.43 no.1
    • /
    • pp.40-52
    • /
    • 2021
  • DNS (Domain Name System) tunnels almost obscure the true network activities of users, which makes it challenging for the gateway or censorship equipment to identify malicious or unpermitted network behaviors. An efficient way to address this problem is to conduct a temporal-spatial analysis on the tunnel traffic. Nevertheless, current studies on this topic limit the DNS tunnel to those with a single protocol, whereas more than one protocol may be used simultaneously. In this paper, we concentrate on the refined identification of two protocols mixed in a DNS tunnel. A feature set is first derived from DNS query and response flows, which is incorporated with deep neural networks to construct a regression model. We benchmark the proposed method with captured DNS tunnel traffic, the experimental results show that the proposed scheme can achieve identification accuracy of more than 90%. To the best of our knowledge, the proposed scheme is the first to estimate the ratios of two mixed protocols in DNS tunnels.

Some Lessons Learned from Previous Studies in Cooperative Driving Automation (협력형 자율주행 기술 개발 동향과 시사점)

  • Jeon, Hyeonmyeong;Yang, Inchul;Kim, Hyoungsoo;Lee, Junhyung;Kim, Sun-Kyum;Jang, Jiyong;Kim, Jiyoon
    • The Journal of The Korea Institute of Intelligent Transport Systems
    • /
    • v.21 no.4
    • /
    • pp.62-77
    • /
    • 2022
  • A cooperative driving automation system is imperative to overcome the limitation of the stand-alone automated driving technology. By definition, a cooperative driving automation system refers to a technology in which an automated vehicle cooperates with other vehicles or infrastructure to increase driving efficiency and safety. Specifically, in this study, the technical elements necessary for the cooperative driving automation technology and the technological research trends were investigated. Subsequently, implications for future cooperative driving automation technology development were drawn through the research trends. Finally, the importance of cooperative driving automation technology and infra-guidance service for automated vehicles were discussed.

Implementation of Pre-Post Process for Accuraty Improvement of OCR Recognition Engine Based on Deep-Learning Technology (딥러닝 기반 OCR 인식 엔진의 정확도 향상을 위한 전/후처리기 기술 구현)

  • Jang, Chang-Bok;Kim, Ki-Bong
    • Journal of Convergence for Information Technology
    • /
    • v.12 no.1
    • /
    • pp.163-170
    • /
    • 2022
  • With the advent of the 4th Industrial Revolution, solutions that apply AI technology are being actively developed. Since 2017, the introduction of business automation solutions using AI-based Robotic Process Automation (RPA) has begun in the financial sector and insurance companies, and recently, it is entering a time when it spreads past the stage of introducing RPA solutions. Among the business automation using these RPA solutions, it is very important how accurately textual information in the document is recognized for business automation using various documents. Such character recognition has recently increased its accuracy by introducing deep learning technology, but there is still no recognition model with perfect recognition accuracy. Therefore, in this paper, we checked how much accuracy is improved when pre- and post-processor technologies are applied to deep learning-based character recognition engines, and implemented RPA recognition engines and linkage technologies.

Software Test Automation Using Data-Driven Approach : A Case Study on the Payment System for Online Shopping (데이터 주도 접근법을 활용한 소프트웨어 테스트 자동화 : 온라인 쇼핑몰 결제시스템 사례)

  • Kim, Sungyong;Min, Daihwan;Rim, Seongtaek
    • Journal of Information Technology Services
    • /
    • v.17 no.1
    • /
    • pp.155-170
    • /
    • 2018
  • This study examines a data-driven approach for software test automation at an online shopping site. Online shopping sites typically change prices dynamically, offer various discounts or coupons, and provide diverse delivery and payment options such as electronic fund transfer, credit cards, mobile payments (KakaoPay, NaverPay, SyrupPay, ApplePay, SamsungPay, etc.) and so on. As a result, they have to test numerous combinations of possible customer choices continuously and repetitively. The total number of test cases is almost 584 billion. This requires somehow automation of tests in settling payments. However, the record playback approach has difficulties in maintaining automation scripts due to frequent changes and complicated component identification. In contrast, the data-driven approach minimizes changes in scripts and component identification. This study shows that the data-driven approach to test automation is more effective than the traditional record playback method. In 2014 before the test automation, the monthly average defects were 5.6 during the test and 12.5 during operation. In 2015 after the test automation, the monthly average defects were 9.4 during the test and 2.8 during operation. The comparison of live defects and detected errors during the test shows statistically significant differences before and after introducing the test automation using the data-driven approach.