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自动化学报和IEEE/CAA JAS两刊编委获得2019年度国家自然科学基金项目

已有 215 次阅读 2019-10-12 10:02 |系统分类:博客资讯

近日,2019年国家自然科学基金评审结果正式揭晓,自动化学报和IEEE/CAA JAS两刊13位编委获得2019年度国家自然科学基金项目!


姓名项目名称/研究领域项目类别
孙长银自主无人系统协同控制理论及应用创新研究群体项目
周志华面向开放动态环境的机器学习创新研究群体项目
贺威仿鸟扑翼飞行机器人基础理论与关键技术重点项目
邓方基于泛在能源的柔性可穿戴传感网系统基础理论与关键技术重点项目
赵勇面向深海温盐深剖面长期监测的高性能光线传感器阵列基础问题研究重点项目
金连文面向数字人文的中文古籍文档图像智能识别与理解重点项目
曾志刚基于忆阻的类人情感生成与演化及其在情感机器人中的应用重点项目
许斌空天往返飞行器智能飞行控制重点项目
王占山复杂互联系统的自适应最优容错控制及其在主动配电网中的应用面上项目
刘艳军不确定非线性偏微分系统的智能自适应边界控制面上项目
刘跃虎无人驾驶环境感知智能的测试模型与可靠性评估面上项目
陈德旺基于人机混合智能的地铁列车增强智能驾驶系统关键算法研究面上项目
董峰多源信息融合油气水多相流流动状态分析与在线监测面上项目


获得2019年度国家自然科学基金项目资助编委论文精选:


基于扰动观测器的机器人自适应神经网络跟踪控制研究

为解决机器人动力学模型未知问题并提升系统鲁棒性,本文基于扰动观测器,考虑动力学模型未知的情况,设计了一种自适应神经网络(Neural network,NN)跟踪控制器.首先分析了机器人运动学和动力学模型,针对模型已知的情况,提出了刚体机械臂通用模型跟踪控制策略;在考虑动力学模型未知的情况下,利用径向基函数(Radial basis function,RBF)神经网络设计基于全状态反馈的自适应神经网络跟踪控制器,并通过设计扰动观测器补偿系统中的未知扰动.利用李雅普诺夫理论证明所提出的控制策略可以使闭环系统误差信号半全局一致有界(Semi-globally uniformly bounded,SGUB),并通过选择合适的增益参数可以将跟踪误差收敛到零域.

于欣波, 贺威, 薛程谦, 孙永坤, 孙长银. 基于扰动观测器的机器人自适应神经网络跟踪控制研究. 自动化学报, 2019, 45(7): 1307-1324.


间接互惠与合作演化的若干问题研究进展

本文所关注的间接互惠是以声望为核心的"下游互惠",具体而言,个体通过帮助他人建立自己在群体中的好声望,从而期待未来获得他人的帮助.可见,声望是"下游互惠"发挥作用的关键.声望的建立引发了两方面的研究:1)如何评价个体声望的好与坏,焦点是何种声望评估准则能够促进合作的演化;2)个体的声望如何在群体中快速、准确、广泛地传播,使得陌生个体间能够获得彼此的声望信息,其中八卦这种声望传播方式成为间接互惠的研究热点之一.基于声望的间接互惠研究前景广阔,未来可能的研究方向主要有复杂网络上的间接互惠、声望传播系统的鲁棒性、声望共享系统的建立和间接互惠在P2P网络中的应用.

张艳玲, 刘爱志, 孙长银. 间接互惠与合作演化的若干问题研究进展. 自动化学报, 2018, 44(1): 1-12.


An Adaptive Strategy via Reinforcement Learning for the Prisoner's Dilemma Game

This paper studies a new adaptive strategy of IPD in different complex networks, where agents can learn and adapt their strategies through reinforcement learning method. A temporal difference learning method is applied for designing the adaptive strategy to optimize the decision making process of the agents. Previous studies indicated that mutual cooperation is hard to emerge in the IPD. Therefore, three examples which based on square lattice network and scale-free network are provided to show two features of the adaptive strategy. First, the mutual cooperation can be achieved by the group with adaptive agents under scale-free network, and once evolution has converged mutual cooperation, it is unlikely to shift. Secondly, the adaptive strategy can earn a better payoff compared with other strategies in the square network. 

Xue Lei, Changyin Sun, Donald Wunsch, Yingjiang Zhou and Yu Fang, "An Adaptive Strategy via Reinforcement Learning for the Prisoner's Dilemma Game," IEEE/CAA J. Autom. Sinica, vol. 5, no. 1, pp. 301-310, Jan. 2018. doi: 10.1109/JAS.2017.7510466


基于分歧的半监督学习

传统监督学习通常需使用大量有标记的数据样本作为训练例,而在很多现实问题中,人们虽能容易地获得大批数据样本,但为数据 提供标记却需耗费很多人力物力.那么,在仅有少量有标记数据时,可否通过对大量未标记数据进行利用来提升学习性能呢?为此,半监督学习 成为近十多年来机器学习的一大研究热点.基于分歧的半监督学习是该领域的主流范型之一,它通过使用多个学习器来对未标记数据进行利用, 而学习器间的"分歧"对学习成效至关重要.本文将综述简介这方面的一些研究进展.

周志华. 基于分歧的半监督学习. 自动化学报, 2013, 39(11): 1871-1878.


扑翼飞行器的建模与控制研究进展

扑翼飞行器(Flapping-wing air vehicle,FAV)即通过模拟昆虫以及鸟类飞行方式而制造的仿生机器人.与常见的固定翼和旋翼飞行器相比,具有效率高、质量轻、机动性强、耗能低等显著优点,是飞行器发展的重要方向.关于扑翼机的研究始于上世纪后期,现如今从理论探索到机体开发都有了可喜的成果.本文首先介绍了世界领先的几款扑翼飞行器的特点,接着简述了扑翼飞行器在动力学、能源、控制等方面的发展现状,并对未来的研究方向做出了展望.

贺威, 丁施强, 孙长银. 扑翼飞行器的建模与控制研究进展. 自动化学报, 2017, 43(5): 685-696.


A Filtering Approach Based on MMAE for a SINS/CNS Integrated Navigation System

This paper explores multiple model adaptive estimation (MMAE) method, and with it, proposes a novel filtering algorithm. The proposed algorithm is an improved Kalman filter-multiple model adaptive estimation unscented Kalman filter (MMAE-UKF) rather than conventional Kalman filter methods, like the extended Kalman filter (EKF) and the unscented Kalman filter (UKF). UKF is used as a subfilter to obtain the system state estimate in the MMAE method. Single model filter has poor adaptability with uncertain or unknown system parameters, which the improved filtering method can overcome. Meanwhile, this algorithm is used for integrated navigation system of strapdown inertial navigation system (SINS) and celestial navigation system (CNS) by a ballistic missile's motion.

Fangfang Zhao, Cuiqiao Chen, Wei He and Shuzhi Sam Ge, "A Filtering Approach Based on MMAE for a SINS/CNS Integrated Navigation System," IEEE/CAA J. Autom. Sinica, vol. 5, no. 6, pp. 1113-1120, Nov. 2018. doi: 10.1109/JAS.2017.7510445 


A Survey of Human-centered Intelligent Robots: Issues and Challenges

Intelligent techniques foster the dissemination of new discoveries and novel technologies that advance the ability of robots to assist and support humans. The human-centered intelligent robot has become an important research field that spans all of the robot capabilities including navigation, intelligent control, pattern recognition and human-robot interaction. This paper focuses on the recent achievements and presents a survey of existing works on human-centered robots. Furthermore, we provide a comprehensive survey of the recent development of the human-centered intelligent robot and discuss the issues and challenges in the field.

Wei He, Zhijun Li and C. L. Philip Chen, "A Survey of Human-centered Intelligent Robots: Issues and Challenges," IEEE/CAA J. Autom. Sinica, vol. 4, no. 4, pp. 602-609, Oct. 2017. doi: 10.1109/JAS.2017.7510604


国家自然科学基金自动化领域数据分析与研究热点变化

本文对国家自然科学基金1986~2017年自动化领域项目申请和资助数据进行了大量数据分析,统计和分析结果表明自动化领域自然科学基金成为研究者重要的研究资金来源,研究人员规模、研究成果数量、基金资助数据都在稳步提升,研究队伍正呈现年轻化趋势.通过数据挖掘30年来不同研究热点及其变化,笔者发现自动化领域基金资助的相关研究领域能紧跟国际国内研究前沿,热点领域中理论研究比重大于应用研究,近年来具有应用研究背景的项目资助比重逐年提高.本文可为广大自动化领域相关的研究者提供选题等方面的借鉴和参考.

邓方, 宋苏, 刘克, 吴国政, 付俊. 国家自然科学基金自动化领域数据分析与研究热点变化. 自动化学报, 2018, 44(2): 377-384.


陆用运动体控制系统发展现状与趋势

在高技术战争的背景下,陆用运动体控制系统呈现出数字化、智能化、网络化、无人化的发展趋势.面向未来作战需求,陆用运动体控制系统必须更加高效、可靠、自主与智能.本文针对陆用运动体控制系统的环境与态势感知,火力指挥与控制,多平台协同以及维修保障与健康管理对当前主要研究成果和最新进展做了简要综述.在总结国内外的现有研究成果的基础上,指出了目前存在的挑战与未来的研究方向.

孙健, 邓方, 陈杰. 陆用运动体控制系统发展现状与趋势. 自动化学报, 2018, 44(11): 1985-1999.



深度学习在手写汉字识别中的应用综述

本文综述了深度学习在手写汉字识别领域的研究进展及具体应用.首先介绍了手写汉字识别的研究背景与现状.其次简要概述了深度学习的几种典型结构模型并介绍了一些主流的开源工具,在此基础上详细综述了基于深度学习的联机和脱机手写汉字识别的方法,阐述了相关方法的原理、技术细节、性能指标等现状情况,最后进行了分析与总结,指出了手写汉字识别领域仍需要解决的问题及未来的研究方向.

金连文, 钟卓耀, 杨钊, 杨维信, 谢泽澄, 孙俊. 深度学习在手写汉字识别中的应用综述. 自动化学报, 2016, 42(8): 1125-1141.


系统H∞范数计算:Lyapunov函数的直接优化方法

研究了李雅普诺夫函数的选择对求解系统H∞范数的影响,提出了一种李雅普诺夫函数的直接优化方法,该方法通过优化黎卡提不等式中的李雅普诺夫函数,给出了H∞范数的通用解析表达式,实现了二阶系统H∞范数的精确求解.不同于需要繁琐优化过程的线性矩阵不等式(Linear matrix inequality,LMI)方法,本文提供了一种有效的途径以直接求解系统H∞范数.

刘秀翀, 王占山. 系统H∞范数计算:Lyapunov函数的直接优化方法. 自动化学报, 2019, 45(8): 1606-1610.


Optimal Control for a Class of Complex Singular System Based on Adaptive Dynamic Programming

This paper presents a new design approach to achieve decentralized optimal control of high-dimension complex singular systems with dynamic uncertainties. Based on robust adaptive dynamic programming (robust ADP) method, controllers for solving the singular systems optimal control problem are designed. The proposed algorithm can work well when the system model is not exactly known but the input and output data can be measured. The policy iteration of each controller only uses their own states and input information for learning, and do not need to know the whole system dynamics. Simulation results on the New England 10-machine 39-bus test system show the effectiveness of the designed controller.

Zhan Shi and Zhanshan Wang, "Optimal Control for a Class of Complex Singular System Based on Adaptive Dynamic Programming," IEEE/CAA J. Autom. Sinica, vol. 6, no. 1, pp. 188-197, Jan. 2019. doi: 10.1109/JAS.2019.1911342  


Refined Jensen-Based Multiple Integral Inequality and Its Application to Stability of Time-Delay Systems

This paper investigates the stability of time-delay systems via a multiple integral approach. Based on the refined Jensen-based inequality, a novel multiple integral inequality is proposed. Applying the multiple integral inequality to estimate the derivative of Lyapunov-Krasovskii functional (LKF) with multiple integral terms, a novel stability condition is formulated for the linear time-delay systems. Two numerical examples are employed to demonstrate the improvements of our results.

Jidong Wang, Zhanshan Wang, Sanbo Ding and Huaguang Zhang, "Refined Jensen-Based Multiple Integral Inequality and Its Application to Stability of Time-Delay Systems," IEEE/CAA J. Autom. Sinica, vol. 5, no. 3, pp. 758-764, Mar. 2018. doi: 10.1109/JAS.2018.7511087


Adaptive Neural Network-Based Control for a Class of Nonlinear Pure-Feedback Systems With Time-Varying Full State Constraints

In this paper, an adaptive neural network (NN) control approach is proposed for nonlinear pure-feedback systems with time-varying full state constraints. The pure-feedback systems of this paper are assumed to possess nonlinear function uncertainties. By using the mean value theorem, pure-feedback systems can be transformed into strict feedback forms. For the newly generated systems, NNs are employed to approximate unknown items. Based on the adaptive control scheme and backstepping algorithm, an intelligent controller is designed. At the same time, time-varying Barrier Lyapunov functions (BLFs) with error variables are adopted to avoid violating full state constraints in every step of the backstepping design. All closedloop signals are uniformly ultimately bounded and the output tracking error converges to the neighborhood of zero, which can be verified by using the Lyapunov stability theorem. Two simulation examples reveal the performance of the adaptive NN control approach.

Tingting Gao, Yan-Jun Liu, Lei Liu and Dapeng Li, "Adaptive Neural Network-Based Control for a Class of Nonlinear Pure-Feedback Systems With Time-Varying Full State Constraints," IEEE/CAA J. Autom. Sinica, vol. 5, no. 5, pp. 923-933, Sept. 2018. doi: 10.1109/JAS.2018.7511195


平行系统方法在自动化集装箱码头中的应用研究

本文采用数据引擎作为人工社会中的基本计算单元,构成一个复杂的平行系统,用于自动化集装箱码头信息控制系统的研究.数据引擎作为一种面向图形化元件组态的计算环境,非常适用于复杂系统的建模与计算.在可视化和动态重构技术的支持下,利用380个数据引擎对一个具有8台岸桥、25辆AGV和16台龙门吊组成的港机系统进行了自动化作业过程的计算实验.研究结果表明,数据引擎技术是实现平行系统的有效方法,由多数据引擎组成的计算环境,能够大幅度降低自动化集装箱码头信息控制系统建模的复杂程度,能够将码头系统的管理和控制过程无缝地融合在一起.该平行系统可直接与港机设备对接,建立“人工码头”和“物理码头”之间的平行关系,从而实现对港机设备的最优控制.

郑松, 吴晓林, 王飞跃, 林东东, 郑蓉, 柯伟林, 池新栋, 陈德旺. 平行系统方法在自动化集装箱码头中的应用研究. 自动化学报, 2019, 45(3): 490-504.




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