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| 1 | A Survey on Deep Learning-based Fine-grained Object Classification and Semantic Segmentation显示文摘The deep learning technology has shown impressive performance in various vision tasks such as image classification, object detection and semantic segmentation. In particular, recent advances of deep learning techniques bring encouraging performance to fine-grained image classification which aims to distinguish subordinate-level categories, such as bird species or dog breeds. This task is extremely challenging due to high intra-class and low inter-class variance. In this paper, we review four types of deep learning based fine-grained image classification approaches, including the general convolutional neural networks(CNNs), part detection based,ensemble of networks based and visual attention based fine-grained image classification approaches. Besides, the deep learning based semantic segmentation approaches are also covered in this paper. The region proposal based and fully convolutional networks based approaches for semantic segmentation are introduced respectively. | Bo Zhao Jiashi Feng Xiao Wu Shuicheng Yan | 2017 | International Journal of Automation and computing2017，14，2： | 36 |
| 2 | Optimal Control of Nonlinear Inverted Pendulum System Using PID Controller and LQR: Performance Analysis Without and With Disturbance Input显示文摘Linear quadratic regulator(LQR) and proportional-integral-derivative(PID) control methods, which are generally used for control of linear dynamical systems, are used in this paper to control the nonlinear dynamical system. LQR is one of the optimal control techniques, which takes into account the states of the dynamical system and control input to make the optimal control decisions.The nonlinear system states are fed to LQR which is designed using a linear state-space model. This is simple as well as robust. The inverted pendulum, a highly nonlinear unstable system, is used as a benchmark for implementing the control methods. Here the control objective is to control the system such that the cart reaches a desired position and the inverted pendulum stabilizes in the upright position. In this paper, the modeling and simulation for optimal control design of nonlinear inverted pendulum-cart dynamic system using PID controller and LQR have been presented for both cases of without and with disturbance input. The Matlab-Simulink models have been developed for simulation and performance analysis of the control schemes. The simulation results justify the comparative advantage of LQR control method. | Lal Bahadur Prasad Barjeev Tyagi Hari Om Gupta | 2014 | International Journal of Automation and computing2014，11，6： | 32 |
| 3 | Minimal Gated Unit for Recurrent Neural Networks显示文摘Recurrent neural networks(RNN) have been very successful in handling sequence data.However,understanding RNN and finding the best practices for RNN learning is a difficult task,partly because there are many competing and complex hidden units,such as the long short-term memory(LSTM) and the gated recurrent unit(GRU).We propose a gated unit for RNN,named as minimal gated unit(MGU),since it only contains one gate,which is a minimal design among all gated hidden units.The design of MGU benefits from evaluation results on LSTM and GRU in the literature.Experiments on various sequence data show that MGU has comparable accuracy with GRU,but has a simpler structure,fewer parameters,and faster training.Hence,MGU is suitable in RNN s applications.Its simple architecture also means that it is easier to evaluate and tune,and in principle it is easier to study MGU s properties theoretically and empirically. | Guo-Bing Zhou Jianxin Wu Chen-Lin Zhang Zhi-Hua Zhou | 2016 | International Journal of Automation and computing2016，13，3： | 30 |
| 4 | Current Researches and Future Development Trend of Intelligent Robot: A Review显示文摘With the advancing of industrialization and the advent of the information age, intelligent robots play an increasingly important role in intelligent manufacturing, intelligent transportation system, the Internet of things, medical health and intelligent services. Based on working experiences in and reviews on intelligent robot studies both in China and abroad, the authors summarized researches on key and leading technologies related to human-robot collaboration, driverless technology, emotion recognition, brain-computer interface, bionic software robot and cloud platform, big data network, etc. The development trend of intelligent robot was discussed, and reflections on and suggestions to intelligent robot development in China were proposed. The review is not only meant to overview leading technologies of intelligent robot all over the world, but also provide related theories, methods and technical guidance to the technological and industrial development of intelligent robot in China. | Tian-Miao Wang Yong Tao Hui Liu | 2018 | International Journal of Automation and computing2018，15，5： | 29 |
| 5 | Implementation of Envelope Analysis on a Wireless Condition Monitoring System for Bearing Fault Diagnosis显示文摘Envelope analysis is an effective method for characterizing impulsive vibrations in wired condition monitoring(CM)systems. This paper depicts the implementation of envelope analysis on a wireless sensor node for obtaining a more convenient and reliable CM system. To maintain CM performances under the constraints of resources available in the cost effective Zigbee based wireless sensor network(WSN), a low cost cortex-M4 F microcontroller is employed as the core processor to implement the envelope analysis algorithm on the sensor node. The on-chip 12 bit analog-to-digital converter(ADC) working at 10 k Hz sampling rate is adopted to acquire vibration signals measured by a wide frequency band piezoelectric accelerometer. The data processing flow inside the processor is optimized to satisfy the large memory usage in implementing fast Fourier transform(FFT) and Hilbert transform(HT). Thus, the envelope spectrum can be computed from a data frame of 2048 points to achieve a frequency resolution acceptable for identifying the characteristic frequencies of different bearing faults. Experimental evaluation results show that the embedded envelope analysis algorithm can successfully diagnose the simulated bearing faults and the data transmission throughput can be reduced by at least 95% per frame compared with that of the raw data, allowing a large number of sensor nodes to be deployed in the network for real time monitoring. | Guo-Jin Feng James Gu Dong Zhen Mustafa Aliwan Feng-Shou Gu Andrew D.Ball | 2015 | International Journal of Automation and computing2015，12，1： | 28 |
| 6 | Comparison of Energy Harvesting Systems for Wireless Sensor Networks显示文摘Wireless sensor networks (WSNs) offer an attractive solution to many environmental, security, and process monitoring problems. However, one barrier to their fuller adoption is the need to supply electrical power over extended periods of time without the need for dedicated wiring. Energy harvesting provides a potential solution to this problem in many applications. This paper reviews the characteristics and energy requirements of typical sensor network nodes, assesses a range of potential ambient energy sources, and outlines the characteristics of a wide range of energy conversion devices. It then proposes a method to compare these diverse sources and conversion mechanisms in terms of their normalised power density. | James M.Gilbert Farooq Balouchi | 2008 | International Journal of Automation and computing2008，5，4： | 25 |
| 7 | Adaptive Iterative Learning Control for Nonlinearly Parameterized Systems with Unknown Time-varying Delay and Unknown Control Direction显示文摘This paper proposes a new adaptive iterative learning control approach for a class of nonlinearly parameterized systems with unknown time-varying delay and unknown control direction.By employing the parameter separation technique and signal replacement mechanism,the approach can overcome unknown time-varying parameters and unknown time-varying delay of the nonlinear systems.By incorporating a Nussbaum-type function,the proposed approach can deal with the unknown control direction of the nonlinear systems.Based on a Lyapunov-Krasovskii-like composite energy function,the convergence of tracking error sequence is achieved in the iteration domain.Finally,two simulation examples are provided to illustrate the feasibility of the proposed control method. | Dan Li Jun-Min Li Department of Mathematics,Xidian University,Xi an 710071,China | 2012 | International Journal of Automation and computing2012，9，6： | 17 |
| 8 | Position Control of Electro-hydraulic Actuator System Using Fuzzy Logic Controller Optimized by Particle Swarm Optimization显示文摘The position control system of an electro-hydraulic actuator system (EHAS) is investigated in this paper. The EHAS is developed by taking into consideration the nonlinearities of the system: the friction and the internal leakage. A variable load that simulates a realistic load in robotic excavator is taken as the trajectory reference. A method of control strategy that is implemented by employing a fuzzy logic controller (FLC) whose parameters are optimized using particle swarm optimization (PSO) is proposed. The scaling factors of the fuzzy inference system are tuned to obtain the optimal values which yield the best system performance. The simulation results show that the FLC is able to track the trajectory reference accurately for a range of values of orifice opening. Beyond that range, the orifice opening may introduce chattering, which the FLC alone is not sufficient to overcome. The PSO optimized FLC can reduce the chattering significantly. This result justifies the implementation of the proposed method in position control of EHAS. | Daniel M. Wonohadidjojo Ganesh Kothapalli Mohammed Y. Hassan | 2013 | International Journal of Automation and computing2013，10，3： | 17 |
| 9 | A Novel Active Learning Method Using SVM for Text Classification显示文摘Support vector machines(SVMs) are a popular class of supervised learning algorithms, and are particularly applicable to large and high-dimensional classification problems. Like most machine learning methods for data classification and information retrieval, they require manually labeled data samples in the training stage. However, manual labeling is a time consuming and errorprone task. One possible solution to this issue is to exploit the large number of unlabeled samples that are easily accessible via the internet. This paper presents a novel active learning method for text categorization. The main objective of active learning is to reduce the labeling effort, without compromising the accuracy of classification, by intelligently selecting which samples should be labeled.The proposed method selects a batch of informative samples using the posterior probabilities provided by a set of multi-class SVM classifiers, and these samples are then manually labeled by an expert. Experimental results indicate that the proposed active learning method significantly reduces the labeling effort, while simultaneously enhancing the classification accuracy. | Mohamed Goudjil Mouloud Koudil Mouldi Bedda Noureddine Ghoggali | 2018 | International Journal of Automation and computing2018，15，3： | 17 |
| 10 | Deep Learning Based Single Image Super-resolution:A Survey显示文摘Single image super-resolution has attracted increasing attention and has a wide range of applications in satellite imaging, medical imaging, computer vision, security surveillance imaging, remote sensing, objection detection, and recognition. Recently, deep learning techniques have emerged and blossomed, producing ' the state-of-the-art” in many domains. Due to their capability in feature extraction and mapping, it is very helpful to predict high-frequency details lost in low-resolution images. In this paper, we give an overview of recent advances in deep learning-based models and methods that have been applied to single image super-resolution tasks. We also summarize, compare and discuss various models from the past and present for comprehensive understanding and finally provide open problems and possible directions for future research. | Viet Khanh Ha Jin-Chang Ren Xin-Ying Xu Sophia Zhao Gang Xie Valentin Masero Amir Hussain | 2019 | International Journal of Automation and computing2019，16，4： | 17 |
| 11 | Stability of Iterative Learning Control with Data Dropouts via Asynchronous Dynamical System显示文摘In this paper, the stability of iterative learning control with data dropouts is discussed. By the super vector formulation, an iterative learning control (ILC) system with data dropouts can be modeled as an asynchronous dynamical system with rate constraints on events in the iteration domain. The stability condition is provided in the form of linear matrix inequalities (LMIS) depending on the stability of asynchronous dynamical systems. The analysis is supported by simulations. | Xu-Hui Bu Zhong-Sheng Hou | 2011 | International Journal of Automation and computing2011，8，1： | 16 |
| 12 | Adaptive Dynamic Surface Control for Integrated Missile Guidance and Autopilot显示文摘Integrated guidance and control for homing missiles utilizing adaptive dynamic surface control approach is considered based on the three channels independence design idea. A time-varying integrated guidance and control model with unmatched uncertainties is first formulated for the pitch channel, and an adaptive dynamic surface control algorithm is further developed to deal with these unmatched uncertainties. It is proved that the proposed feedback controller can ensure not only the accuracy of target interception, but also the stability of the missile dynamics. Then, the same control approach is further applied to the control design of the yaw and roll channels. The 6-degree-of-freedom (6-DOF) nonlinear missile simulation results demonstrate the feasibility and advantage of the proposed integrated guidance and control design scheme. | Ming-Zhe Hou Guang-Ren Duan | 2011 | International Journal of Automation and computing2011，8，1： | 16 |
| 13 | Fuzzy PID Control of Space Manipulator for Both Ground Alignment and Space Applications显示文摘Considering gravity change from ground alignment to space applications, a fuzzy proportional-integral-differential(PID)control strategy is proposed to make the space manipulator track the desired trajectories in different gravity environments. The fuzzy PID controller is developed by combining the fuzzy approach with the PID control method, and the parameters of the PID controller can be adjusted on line based on the ability of the fuzzy controller. Simulations using the dynamic model of the space manipulator have shown the effectiveness of the algorithm in the trajectory tracking problem. Compared with the results of conventional PID control,the control performance of the fuzzy PID is more effective for manipulator trajectory control. | Fu-Cai Liu Li-Huan Liang Juan-Juan Gao | 2014 | International Journal of Automation and computing2014，11，4： | 16 |
| 14 | Adversarial Attacks and Defenses in Images, Graphs and Text: A Review显示文摘Deep neural networks(DNN)have achieved unprecedented success in numerous machine learning tasks in various domains.However,the existence of adversarial examples raises our concerns in adopting deep learning to safety-critical applications.As a result,we have witnessed increasing interests in studying attack and defense mechanisms for DNN models on different data types,such as images,graphs and text.Thus,it is necessary to provide a systematic and comprehensive overview of the main threats of attacks and the success of corresponding countermeasures.In this survey,we review the state of the art algorithms for generating adversarial examples and the countermeasures against adversarial examples,for three most popular data types,including images,graphs and text. | Han Xu Yao Ma Hao-Chen Liu Debayan Deb Hui Liu Ji-Liang Tang Anil K.Jain | 2020 | International Journal of Automation and computing2020，17，2： | 15 |
| 15 | Adaptive Terminal Sliding Mode Control for Rigid Robotic Manipulators显示文摘In order to apply the terminal sliding mode control to robot manipulators,prior knowledge of the exact upper bound of parameter uncertainties,and external disturbances is necessary.However,this bound will not be easily determined because of the complexity and unpredictability of the structure of uncertainties in the dynamics of the robot.To resolve this problem in robot control,we propose a new robust adaptive terminal sliding mode control for tracking problems in robotic manipulators.By applying this adaptive controller,prior knowledge is not required because the controller is able to estimate the upper bound of uncertainties and disturbances.Also,the proposed controller can eliminate the chattering effect without losing the robustness property.The stability of the control algorithm can be easily verified by using Lyapunov theory.The proposed controller is tested in simulation on a two-degree-of-freedom robot to prove its effectiveness. | Mezghani Ben Romdhane Neila Damak Tarak | 2011 | International Journal of Automation and computing2011，8，2： | 15 |
| 16 | Observer-based Adaptive Fuzzy Control for a Class of Nonlinear Time-delay Systems显示文摘An observer-based adaptive fuzzy control is presented for a class of nonlinear systems with unknown time delays. The state observer is first designed, and then the controller is designed via the adaptive fuzzy control method based on the observed states. Both the designed observer and controller are independent of time delays. Using an appropriate Lyapunov-Krasovskii functional, the uncertainty of the unknown time delay is compensated, and then the fuzzy logic system in Mamdani type is utilized to approximate the unknown nonlinear functions. Based on the Lyapunov stability theory, the constructed observer-based controller and the closed-loop system are proved to be asymptotically stable. The designed control law is independent of the time delays and has a simple form with only one adaptive parameter vector, which is to be updated on-line. Simulation results are presented to demonstrate the effectiveness of the proposed approach. | Hassan A. Yousef Mohamed Hamdy | 2013 | International Journal of Automation and computing2013，10，4： | 15 |
| 17 | Gesture Recognition Based on BP Neural Network Improved by Chaotic Genetic Algorithm显示文摘Aim at the defects of easy to fall into the local minimum point and the low convergence speed of back propagation(BP)neural network in the gesture recognition, a new method that combines the chaos algorithm with the genetic algorithm(CGA) is proposed. According to the ergodicity of chaos algorithm and global convergence of genetic algorithm, the basic idea of this paper is to encode the weights and thresholds of BP neural network and obtain a general optimal solution with genetic algorithm, and then the general optimal solution is optimized to the accurate optimal solution by adding chaotic disturbance. The optimal results of the chaotic genetic algorithm are used as the initial weights and thresholds of the BP neural network to recognize the gesture. Simulation and experimental results show that the real-time performance and accuracy of the gesture recognition are greatly improved with CGA. | Dong-Jie Li Yang-Yang Li Jun-Xiang Li Yu Fu | 2018 | International Journal of Automation and computing2018，15，3： | 14 |
| 18 | Delay-range-dependent Stability Criterion for Interval Time-delay Systems with Nonlinear Perturbations显示文摘In this paper, we consider the problem of robust stability for a class of linear systems with interval time-varying delay under nonlinear perturbations using Lyapunov-Krasovskii (LK) functional approach. By partitioning the delay-interval into two segments of equal length, and evaluating the time-derivative of a candidate LK functional in each segment of the delay-interval, a less conservative delay-dependent stability criterion is developed to compute the maximum allowable bound for the delay-range within which the system under consideration remains asymptotically stable. In addition to the delay-bi-segmentation analysis procedure, the reduction in conservatism of the proposed delay-dependent stability criterion over recently reported results is also attributed to the fact that the time-derivative of the LK functional is bounded tightly using a newly proposed bounding condition without neglecting any useful terms in the delay-dependent stability analysis. The analysis, subsequently, yields a stable condition in convex linear matrix inequality (LMI) framework that can be solved non-conservatively at boundary conditions using standard numerical packages. Furthermore, as the number of decision variables involved in the proposed stability criterion is less, the criterion is computationally more effective. The effectiveness of the proposed stability criterion is validated through some standard numerical examples. | K.Ramakrishnan G.Ray | 2011 | International Journal of Automation and computing2011，8，1： | 14 |
| 19 | Cooperative Formation Control of Autonomous Underwater Vehicles:An Overview显示文摘Formation control is a cooperative control concept in which multiple autonomous underwater mobile robots are deployed for a group motion and/or control mission.This paper presents a brief review on various cooperative search and formation control strategies for multiple autonomous underwater vehicles(AUV) based on literature reported till date.Various cooperative and formation control schemes for collecting huge amount of data based on formation regulation control and formation tracking control are discussed.To address the challenge of detecting AUV failure in the fleet,communication issues,collision and obstacle avoidance are also taken into attention.Stability analysis of the feasible formation is also presented.This paper may be intended to serve as a convenient reference for the further research on formation control of multiple underwater mobile robots. | Bikramaditya Das Bidyadhar Subudhi Bibhuti Bhusan Pati | 2016 | International Journal of Automation and computing2016，13，3： | 14 |
| 20 | Modeling and Control of Hybrid Machine Systems—a Five-bar Mechanism Case显示文摘一台混合机器(HM ) 作为一台典型 mechantronic 设备,是一个有用工具产生光滑的运动,并且借助于机械连接机制把一台大经常的速度马达的运动与一台小伺服马达相结合,以便提供一个强大的可编程的开车系统。为了完成,设计目的,一个控制系统被要求。设计一个更好的控制系统并且分析 HM 的性能,一个动态模型是必要的。这份报纸首先用 Lagrangian 明确的表达与五酒吧的机制开发 HM 的一个动态模型。然后,在系统分析很有用的几个重要性质,和控制系统设计,被介绍。基于发达动态模型,二条控制途径,计算转矩,和联合计算转矩和幻灯片模式控制,被采用控制 HM 系统。模拟结果表明控制表演,每控制的限制来临。关键词混合机器(HM )- Lagrangian 系统 - 动力学 - 计算转矩控制 - 滑动模式控制工作被 EPSRC 研究委员会部分地支持(没有。GR/M29108/01 ) 。于洪年是在 Staffordshire 大学的计算机科学的一个教授。他在 Yanshan 大学是在控制和系统工程的一个讲师,中国,从 1985 鈥? 990 ,他在国王鈥檚 学院伦敦在机器人学进行了博士( 1990 鈥? 994 ),并且是在在萨西克斯郡大学生产系统的一个研究家伙( 1994 鈥? 996 ),在在利物浦约翰·穆尔鈥檚 大学的人工智能的一个讲师( 1996 鈥? 999 ),在在 Exeter 的大学的控制和系统工程的一个讲师( 1999 鈥? 002 ),并且在在 Bradford 的大学的计算的一个高级讲师( 200 他现在在 Staffordshire 大学带移动计算和分布式的系统研究组。他在 Bradford 的大学是安排的建模优化和聪明的控制研究组的一个成立成员。他出版了集中于下列的超过 100 篇研究论文:混合机器的神经网络,计算机网络,机器人操纵者的适应、柔韧的控制,分析和控制,时间的控制推迟了系统,预兆的控制,生产系统建模并且安排,计划,并且供应链。他在神经网络有广泛的研究经验,移动计算,建模,机器人操纵者的控制;并且建模,安排,计划,并且大分离事件的模拟有在生产系统,供应链,交通网络,和计算机网络的应用程序的动态系统。于教授是一个 EPSRC 学院成员, IEEE 的一个成员,和为几个会议和杂志编委的一位委员。他从 EPSRC,皇家学会,和 EU,以及从工业保持了几研究资助。他被 IEE 委员会在 1997 在机器人操纵者的适应、柔韧的控制上为他的论文授于 F.C 威廉奖赏。 | Hongnian Yu | 2006 | International Journal of Automation and computing2006，3，3： | 13 |
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