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第36届中国控制会议

作者： Jian Wang Huimin Miao System Engineering Institute School of AutomationHuazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Hubei Province Key Laboratory of Systems Science in Metallurgical Process Wuhan University of Science and Technology

ISBN: (纸本)9781538629185

Nowadays,many researches study the negotiation-based order allocation problem in the supply chain environment,aiming to improve the efficiency of the allocation and the profits of the supply chain *** competition and cooperation in supplier’s side are mainly addressed because of independent *** this paper,we analyze an interdependent order allocation problem in a two-echelon supply *** supply chain consists of a manufacturer echelon and a supplier *** to the interdependence,both the competition and cooperation in the manufacturer echelon are *** agent-based negotiation algorithm is developed to support the order allocation process and the conflicts *** show in experiments that orders under various supply chain contexts can be successfully allocated through the algorithm.

关键词： Supply chain system order allocation agent-based negotiation

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A double-integrator system for distributed optimization of convex cost functions 29

A double-integrator system for distributed optimization of c...

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第29届中国控制与决策会议

作者： Ngoc-Tu Tran Xuan Feng Wen-Yuan Xu Na Zhan Xi Wang School of Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control(Huazhong University of Science and Technology) Ministry of Education Hubei Electric Power Company

ISBN: (纸本)9781509046584

In this paper,the distributed optimization problem is investigated under a second-order multi-agent *** the proposed algorithm,each agent solves the optimization via local computation and information exchange with its neighbors through the communication ***,in comparison with the existing second-order distributed optimization algorithms,the proposed algorithm is much simpler due to one coupled information exchange among the agents is *** achieve the optimization,the distributed algorithm is proposed based on the consensus method and the gradient *** optimal solution of the problem is thus obtained with the design of Lyapunov function and the help of LaSallel's Invariance Principle.A numerical simulation example and comparison of proposed algorithm with existing works are presented to illustrate the effectiveness of the theoretical result.

关键词： Second-order multi-agent systems Distributed optimization Consensus Lyapunov function Gradient algorithm

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Protecting privacy of users in brain-computer interface applications

arXiv

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arXiv 2019年

作者： Agarwal, Anisha Dowsley, Rafael McKinney, Nicholas D. Wu, Dongrui Lin, Chin-Teng De Cock, Martine Nascimento, Anderson C.A. School of Engineering and Technology University of Washington TacomaWA98402 United States Department of Computer Science Bar-Ilan University Israel School of Engineering and Technology University of Washington TacomaWA98402 United States Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan China School of Software University of Technology Sydney Australia Department of Applied Mathematics Computer Science and Statistics Ghent University Ghent9000 Belgium

Machine learning (ML) is revolutionizing research and industry. Many ML applications rely on the use of large amounts of personal data for training and inference. Among the most intimate exploited data sources is electroencephalogram (EEG) data, a kind of data that is so rich with information that application developers can easily gain knowledge beyond the professed scope from unprotected EEG signals, including passwords, ATM PINs, and other intimate data. The challenge we address is how to engage in meaningful ML with EEG data while protecting the privacy of users. Hence, we propose cryptographic protocols based on Secure Multiparty Computation (SMC) to perform linear regression over EEG signals from many users in a fully privacy-preserving (PP) fashion, i.e. such that each individual's EEG signals are not revealed to anyone else. To illustrate the potential of our secure framework, we show how it allows estimating the drowsiness of drivers from their EEG signals as would be possible in the unencrypted case, and at a very reasonable computational cost. Our solution is the first application of commodity-based SMC to EEG data, as well as the largest documented experiment of secret sharing based SMC in general, namely with 15 players involved in all the computations. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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An improved proxy-based sliding mode control method for a wearable wrist exoskeleton

IPPTA: Quarterly Journal of Indian Pulp and Paper Technical ...

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IPPTA: Quarterly Journal of Indian Pulp and Paper Technical Association 2018年第1期30卷 458-467页

作者： Tu, Xikai Wu, Sai Li, Jialu Huang, Ming School of Mechanical Engineering Hubei University of Technology Wuhan China School of Industrial Design Hubei University of Technology Wuhan China School of Mechatronic Engineering Jiangsu Institute of Technology Changzhou China MOE Key Laboratory of Image Processing and Intelligence Control Huazhong University of Science and Technology Wuhan China

In order to improve the safety and adaptability during the robot-assisted rehabilitation of wrist joint, a wearable wrist exoskeleton rehabilitation device driven by pneumatic muscles is developed, and its control method is a new modified proxy-based sliding mode control (PSMC) strategy. PSMC created by Ryo Kikuuwe and Hideo Fujimoto, combines good tracking with control safety so it is well suitable for pneumatic muscle actuators. This paper build the dynamics models and compares the two kinds of modified PSMC with PSMC methods applied to the wrist rehabilitation exoskeleton. Experimental results demonstrate that the improved PSMC method performs better on tracking and less little degradation on safety when the system lies in a condition of uncertain resistance and changeable load. © 2018 Indian Pulp and Paper Technical Association. All rights reserved.

关键词： Sliding mode control

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A Geometric Approach to Second-Order Consensus of Heterogeneous Networked Systems

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IEEE Transactions on Cybernetics 2018年 2018 Jan 9页

作者： Su, Housheng Ye, Yanyan Chen, Xia He, Haibo School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China. China China Department of Electrical Computer and Biomedical Engineering University of Rhode Island Kingston RI 02881 USA. United States

This paper investigates second-order consensus of networked systems with heterogeneous intrinsic nonlinear dynamics via a geometrical method, in which the nonlinear dynamics are governed by both velocity and position. First, two necessary conditions are deduced for the existence of consensus solutions by analyzing the inherent nonlinear dynamics of isolated nodes. Then a closed invariant set is constructed via geometrical methods. The nonempty of the set implies the existence of consensus solution. Assuming that the primary and the second dimension about the above invariant set are the same linear subspace, the system can be divided into two simple subsystems through a linear transformation. In addition, some sufficient conditions are proposed for reaching the global consensus based on matrix theory and Lyapunov method. Finally, numerical simulation results are provided to illustrate the validity of theoretical analysis. IEEE

关键词： Multi agent systems

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Multi-objective optimization for ladle tracking of aluminium tapping based on NSGA-II 1

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12th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2017

作者： Zhou, Kaibo Zou, Yutao Wang, Hongting Xu, Gaofeng Guo, Sihai School of Automation Huazhong University of Science and Technology Wuhan430074 China MOE Key Laboratory of Image Processing and Intelligence Control Wuhan430074 China School of Automation Wuhan University of Technology Wuhan430070 China

ISBN: (数字)9789811071799

ISBN: (纸本)9789811071782

In order to realize the optimization of ladle tracking of aluminium tapping, a mathematical model, which takes the grade of aluminium, the energy required for transportation and the optimum ratio of aluminium liquid into account, is established. The traditional method optimizes the impurity content and the transport distance based on a single objective optimization, but it requires the empirical values of the weight coefficients. The paper proposes a modified multi-objective optimization model with the elitist non-dominated sorting genetic algorithm (NSGA-II). In the crossover operator process and the mutation operator process, the separately improved methods are introduced based on the ladle tracking problem of aluminium tapping, which replaces the Simulated Binary Crossover (SBX) in the original NSGA-II algorithm into Partially Matched Crossover (PMX) based on natural number coding and uses exchange mutation (EM) operator. Finally, the practical production data of the aluminium factory is used to verify the validity and practicability of the method, and the results show that this method can obtain a feasible solution for the user to choose suitable solutions, and avoid the defects of selecting empirical weighting coefficient. © Springer Nature Singapore Pte Ltd 2017.

关键词： Multiobjective optimization

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Fault diagnosis in aluminium electrolysis using a joint method based on kernel principal component analysis and support vector machines 12th

Fault diagnosis in aluminium electrolysis using a joint meth...

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12th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2017

作者： Zhou, Kaibo Xu, Gaofeng Wang, Hongting Guo, Sihai School of Automation Huazhong University of Science and Technology Wuhan430074 China MOE Key Laboratory of Image Processing and Intelligence Control Wuhan430074 China School of Automation Wuhan University of Technology Wuhan430070 China

ISBN: (纸本)9789811071782

As a key part of aluminium smelting, the operational conditions of aluminium electrolytic cells are of great significance for the stability of the aluminium electrolysis process. As a result, developing a effective process monitoring and multiple fault diagnosis model is essential. Traditional multi-classification methods such as neural networks and multiple support vector machines (multi-SVM) have good effects. However, the connatural limitations of these methods limit the prediction accuracies. To solve this problem, a hierarchical method for multiple fault diagnosis based on kernel principal component analysis (KPCA) and support vector machines (SVM) is proposed in this paper. Firstly, test statistics, such as the comprehensive index , the squared prediction error (SPE), and Hotellings T-squared (T2), are used for fault detection. To separate faults preliminarily, traditional K-means clustering as transition layer is applied to the principal component scores. Next, anode effect is recognized and classified by the established SVM prediction model. Compared with multi-SVM-based classification methods, the proposed hierarchical method can diagnosis different faults with a higher precision. The prediction accuracy can reach about 90%. © Springer Nature Singapore Pte Ltd 2017.

关键词： Support vector machines

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A General End-to-end Diagnosis Framework for Manufacturing Systems

arXiv

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arXiv 2018年

作者： Yuan, Ye Ma, Guijun Cheng, Cheng Zhou, Beitong Zhao, Huan Zhang, Hai-Tao Ding, Han State Key Lab of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China School of Artificial Intelligence and Automation MOE Key Lab of Intelligent Control and Image Processing Huazhong University of Science and Technology Wuhan430074 China School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan430074 China

The manufacturing sector is envisioned to be heavily influenced by artificial intelligence-based technologies with the extraordinary increases in computational power and data volumes1,2. A central challenge in manufacturing sector lies in the requirement of a general framework to ensure satisfied diagnosis and monitoring performances in different manufacturing applications. Here we propose a general data-driven, end-to-end framework for the monitoring of manufacturing systems. This framework, derived from deep learning techniques, evaluates fused sensory measurements to detect and even predict faults and wearing conditions. This work exploits the predictive power of deep learning to automatically extract hidden degradation features from noisy, time-course data. We have experimented the proposed framework on ten representative datasets drawn from a wide variety of manufacturing applications. Results reveal that the framework performs well in examined benchmark applications and can be applied in diverse contexts, indicating its potential use as a critical corner stone in smart manufacturing. Copyright © 2018, The Authors. All rights reserved.

关键词： Manufacture

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Region stability analysis and tracking control of memristive recurrent neural network

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Neural networks : the official journal of the International Neural Network Society 2018年 98卷 51-58页

作者： Gang Bao Zhigang Zeng Yanjun Shen Hubei Key Laboratory of Cascaded Hydropower Stations Operation & Control Electrical Engineering & New Energy China Three Gorges University Yichang 443002 China. Electronic address: ctgugangbao@***. China School of Automation Huazhong University of Science and Technology Wuhan Hubei 430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China. Electronic address: zgzeng@***. Hubei Key Laboratory of Cascaded Hydropower Stations Operation & Control Electrical Engineering & New Energy China Three Gorges University Yichang 443002 China. Electronic address: shenyj@***.

Memristor is firstly postulated by Leon Chua and realized by Hewlett-Packard (HP) laboratory. Research results show that memristor can be used to simulate the synapses of neurons. This paper presents a class of recurrent neural network with HP memristors. Firstly, it shows that memristive recurrent neural network has more compound dynamics than the traditional recurrent neural network by simulations. Then it derives that n dimensional memristive recurrent neural network is composed of [Formula: see text] sub neural networks which do not have a common equilibrium point. By designing the tracking controller, it can make memristive neural network being convergent to the desired sub neural network. At last, two numerical examples are given to verify the validity of our result.

关键词： Memristive neural network Memristor Stability

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Fast signal recovery from saturated measurements by linear loss and nonconvex penalties

arXiv

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arXiv 2018年

作者： He, Fan Huang, Xiaolin Liu, Yipeng Yan, Ming Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University The MOE Key Laboratory of System Control and Information Processing Shanghai200240 China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China The Department of Computational Mathematics Science and Engineering Michigan State University MI United States

Sign information is the key to overcoming the inevitable saturation error in compressive sensing systems, which causes information loss and results in bias. For sparse signal recovery from saturation, we propose to use a linear loss to improve the effectiveness from existing methods that utilize hard constraints/hinge loss for sign consistency. Due to the use of linear loss, an analytical solution in the update progress is obtained, and some nonconvex penalties are applicable, e.g., the minimax concave penalty, the 0 norm, and the sorted 1 norm. Theoretical analysis reveals that the estimation error can still be bounded. Generally, with linear loss and nonconvex penalties, the recovery performance is significantly improved, and the computational time is largely saved, which is verified by the numerical experiments. Copyright © 2018, The Authors. All rights reserved.

关键词： Compressed sensing

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