检索结果-内蒙古大学图书馆

Annual Conference of the IEEE Industrial Electronics Society

作者： Luefeng Chen Mengtian Zhou Min Wu Jinhua She Kaoru Hirota School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei China School of Engineering Tokyo University of Technology Tokyo Japan Tokyo Institute of Technology Beijing Institute of Technology Yokohama Japan

A two-layer fuzzy kernel regression (TLFKR) model is proposed for understanding human emotional intention in human-robot interaction, where TLFKR model consists of two layers, including fuzzy c-means (FCM) with kernel ridge regression (Kernel 1) for information analysis layer, fuzzy support vector regressions (FSVR) (Kernel 2) for intention understanding layer. TLFKR model represents the weight impact for each emotional information and aims to improve smooth human-robot interaction by endowing robot with human emotional intention understanding capability. Experimental Results show that the proposal obtains an intention understanding accuracy of 65.67%/68.33%/80.67% with the clusters number c=2/3/6 (according to different genders/ages/nationalities), which are 7.34%/7.18%/8.67% and 18.67%/21.33%/33.67% higher than that of TLFSVR and SVR, respectively. Additionally, preliminary application experiments are performed in the developing emotional social robot system, where two mobile robots and volunteers experience a scenario of "drinking at a bar", and social robots are able to express basic emotions and understand human order intention.

关键词： Kernel Robots Training Support vector machines Proposals Information analysis Bars

来源：评论

学校读者我要写书评

暂无评论

Speech emotion recognition based on deep belief networks and wavelet packet cepstral coefficients

引用

International Journal of Simulation: systems, Science and Technology 2016年第28期17卷 28.1-28.5页

作者： Huang, Yongming Wu, Ao Zhang, Guobao Li, Yue School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China

A wavelet packet based adaptive filter-bank construction combined with Deep Belief Network(DBN) feature learning method is proposed for speech signal processing in this paper. On this basis, a set of acoustic features are extracted for speech emotion recognition, namely Coiflet Wavelet Packet Cepstral Coefficients (CWPCC). CWPCC extends the conventional Mel-Frequency Cepstral Coefficients (MFCC) by adapting the filter-bank structure according to the decision task. And Deep Belief Networks (DBNs) are artificial neural networks having more than one hidden layer, which are first pre-trained layer by layer and then fine-tuned using back propagation algorithm. The well-trained deep neural networks are capable of modeling complex and non-linear features of input training data and can better predict the probability distribution over classification labels. Speech emotion recognition system is constructed with the feature set, DBNs feature learning structure and Support Vector Machine as classifier. Experimental results on Berlin emotional speech database show that the Coiflet Wavelet Packet is more suitable in speech emotion recognition than other acoustics features and proposed DBNs feature learning structure combined with CWPCC improve emotion recognition performance over the conventional emotion recognition method. © 2016, UK Simulation Society. All rights reserved.

关键词： Filter banks

来源：评论

学校读者我要写书评

暂无评论

Pedestrian Detection via Contour Fragments

Pedestrian Detection via Contour Fragments

引用

第35届中国控制会议

作者： Dandi Chen Siyu Xia Yuan Zhou Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Computer Science and Engineering Department University of Connecticut

ISBN: (纸本)9781509009107

Pedestrian detection has been the key point of several hot research fields,including intelligent surveillance,driving assistance,intelligent robot,*** to pedestrian appearance,multi-pose,angle of view,environment and other factors,the existing pedestrian detection algorithms still have some unsolved technical *** this paper,we focus on contour *** on traditional feature descriptors and feature selection methods,we proposed a novel oriented Chamfer distance(OCD) feature to describe pedestrian *** improves anti-interference ability of image noise using Bag of Words(BOW)model and image multi-scale ***,we conducted experimental comparisons using scale-invariant feature transform(SIFT),histogram of oriented gradient(HOG),speeded up robust feature(SURF) and OCD feature in feature extraction and parameter optimization,in Boosting and support vector machine(SVM) classification *** results demonstrate that the proposed OCD feature has great discriminant ability of pedestrian contours.

关键词： Pedestrian detection Contour feature Oriented Chamfer distance feature Support vector machine Boosting

来源：评论

学校读者我要写书评

暂无评论

Data-Based Robust control for Unknown Nonlinear systems 35

Data-Based Robust Control for Unknown Nonlinear Systems

引用

第35届中国控制会议

作者： YANG Xiong LIU Derong WEI Qinglai School of Electrical Engineering and Automation Tianjin University School of Automation and Electrical Engineering University of Science and Technology Beijing The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

ISBN: (纸本)9781509009107

In this paper, we develop a data-based robust control method for a class of unknown nonlinear systems with input constraints. First, we transform the robust control problem into a constrained optimal control problem by introducing a value function for the nominal system. Then, under the framework of integral reinforcement learning, we construct an actor-critic architecture to approximately solve the constrained optimal control problem. Based on the present architecture, we only require system data rather than the availability of full/partial prior knowledge of system dynamics. In addition, by using Lyapunov's direct method, we prove that the obtained approximate optimal control can guarantee the unknown nonlinear system to be uniformly ultimately bounded. Finally, we provide an example to illustrate the effectiveness of the developed method.

关键词： Constrained input Integral reinforcement learning Nonlinear systems Optimal control Robust control

来源：评论

学校读者我要写书评

暂无评论

On stability of sampled-data extended state observer for networked systems

On stability of sampled-data extended state observer for net...

引用

Asian control Conference

作者： Yuan Huang Junzheng Wang Dawei Shi Jian Xue State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing P. R. China Harvard John A. Paulson School of Engineering & Applied Sciences Harvard University Cambridge MA USA

ISBN: (纸本)9781509015740;9781509015733

The problem of sampled-data state observation is considered in this work. A nonlinear continuous-time system with internal uncertainty and external disturbance is introduced, for which the sampled-data observation problem based on an extended state observer is formulated. We first introduce the framework of the observed system, in which the output measurement is sampled and transmitted to extended state observer periodically. Then based on this framework, the observation performance of the sampled-data extended state observer (SD-ESO) is investigated. For the observer considered, the uniformly ultimately bounded property has been guaranteed. Furthermore, a co-design method for the sample interval and high gain parameter of SD-ESO is provided to achieve the desired observation performance. The obtained theoretic results are validated through the numerical simulations.

关键词： Observers Uncertainty Networked control systems Convergence Distributed databases Gold Australia

来源：评论

学校读者我要写书评

暂无评论

An algorithm for assembly job shop scheduling problem

An algorithm for assembly job shop scheduling problem

引用

2016 2nd International Conference on Electronics,Network and Computer engineering(ICENCE 2016)

作者： Xiao-Qin Wan Hong-Sen Yan School of Automation Southeast University MOE Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University

ISBN: (纸本)9781510830073

The problem of assembly job shop scheduling(AJSS) is studied with the objective of minimizing the weighted sum of earliness and tardiness penalties. An insertion search algorithm is proposed to solve the problem. The operations of job with tardiness or earliness are shifted left or right to optimize the sequence. Simulation results validate the effectiveness of the proposed model and algorithm.

关键词： Assembly job shop tardiness earliness

来源：评论

学校读者我要写书评

暂无评论

Towards quality advancement of underwater machine vision with generative adversarial networks

arXiv

引用

arXiv 2017年

作者： Chen, Xingyu Yu, Junzhi Kong, Shihan Wu, Zhengxing Fang, Xi Wen, Li University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Mechanical Engineering and Automation Beihang University Beijing100191 China

Underwater machine vision has attracted significant attention, but its low quality has prevented it from a wide range of applications. Although many different algorithms have been developed to solve this problem, real-time adaptive methods are frequently deficient. In this paper, based on filtering and the use of generative adversarial networks (GANs), two approaches are proposed for the aforementioned issue, i.e., a filteringbased restoration scheme (FRS) and a GAN-based restoration scheme (GAN-RS). Distinct from previous methods, FRS restores underwater images in the Fourier domain, which is composed of a parameter search, filtering, and enhancement. Aiming to further improve the image quality, GAN-RS can adaptively restore underwater machine vision in real time without the need for pretreatment. In particular, information in the Lab color space and the dark channel is developed as loss functions, namely, underwater index loss and dark channel prior loss, respectively. More specifically, learning from the underwater index, the discriminator is equipped with a carefully crafted underwater branch to predict the underwater probability of an image. A multi-stage loss strategy is then developed to guarantee the effective training of GANs. Through extensive comparisons on the image quality and applications, the superiority of the proposed approaches is confirmed. Consequently, the GAN-RS is considerably faster and achieves a state-of-the-art performance in terms of the color correction, contrast stretch, dehazing, and feature restoration of various underwater scenes. The source code will be made available. Copyright © 2017, The Authors. All rights reserved.

关键词： Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

Distributed Consensus Tracking control for Multiple Simple-Pendulum Network systems 35

Distributed Consensus Tracking Control for Multiple Simple-P...

引用

第35届中国控制会议

作者： JIANG Yulian WANG Shenquan LI Yuanchun LIU Derong College of Electrical and Electronic Engineering Changchun University of Technology The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Automation and Electrical Engineering University of Science and Technology Beijing

ISBN: (纸本)9781509009107

This paper investigates the consensus tracking problem for networked control systems consisting of multiple simplependulums driven by corresponding DC motors.A distributed adaptive consensus control algorithm is developed to guarantee the state tracking for each simple-pendulum with nonlinear *** dynamic model of networked simple-pendulums driven by DC motors is obtained first,and the mathematical description of consensus tracking control problem for multi-agent system is ***,fully distributed consensus tracking protocol without any global information is designed by using adaptive control technology to adjust the coupling weights between neighboring ***,simulation results demonstrate the effectiveness of the proposed consensus tracking control algorithm.

关键词： consensus tracking simple-pendulum network system adaptive control nonlinear dynamics multi-agent system

来源：评论

学校读者我要写书评

暂无评论

Adaptive critic designs for solving event-based H∞ control problems

Adaptive critic designs for solving event-based H∞ control ...

引用

American control Conference

作者： Ding Wang Chaoxu Mu Derong Liu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China the School of Electrical and Information Engineering Tianjin University Tianjin 300072 China the School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China

ISBN: (纸本)9781509045839

In this paper, the adaptive critic method is applied to solve a class of continuous-time event-based H_∞ control problems. The present control problem is transformed into a two-player zero-sum differential game and the adaptive critic structure is employed for coping with the event-based minimax optimization. Next, the event-based optimal feedback control and the time-based worst-case disturbance law are learned by training a critic neural network. In addition, the closed-loop system is constructed with stability analysis of the critic error dynamics and the sampled-data plant. The exclusion of the infamous Zeno behavior of the present event-based control design is also discussed. Finally, the control performance of the present approach is evaluated through simulation study.

关键词： exclusion infamous Zeno exclusion critic Event-based Data sampling control performance design control

来源：评论

学校读者我要写书评

暂无评论

External consensus of networked multi-agent systems with nonlinear dynamics and random network delay

External consensus of networked multi-agent systems with non...

引用

Asian control Conference

作者： Qi Lei Jia-Hui Li Guo-Ping Liu Min Wu School of Information Science and Engineering University of Central South University Changsha China School of Engineering University of South Wales Pontypridd U.K. School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control Intelligent Automation for Complex Systems Wuhan China

ISBN: (纸本)9781509015740;9781509015733

In this paper, the external consensus problem of networked multi-agent systems with fixed undirected topology, random network delay and nonlinear dynamics is considered. The unknown nonlinear dynamics existing in the systems can be described as RBF-ARX model. Besides, the random network delay can be compensated by introducing the prediction strategy. The RBF-ARX model is used as prediction model to design the output predictor, which is to generate the prediction sequence of control input and agent's output. Then, the designed selector chooses the proper value from the available sequences corresponding to the value of the network delay. Based on the mentioned above, a distributed external consensus control algorithm is proposed to make the considered systems with external reference input achieve consensus. Finally, an example is given to illustrate the validity of the proposed algorithm.

关键词： Delays Nonlinear dynamical systems Algorithm design and analysis Prediction algorithms Predictive models Network topology Radial basis function networks

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：