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第三十九届中国控制会议

作者： Xianwei Li Yang Tang Shaoyuan Li Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology

This paper focuses on designing dynamic event-triggered(DET) protocols for consensus control of general linear multi-agent systems(MASs). Design algorithms are constructed for DET protocols with static and adaptive coupling, respectively. The designed event-triggering conditions involve internal dynamic variables that depend on the error information of the system, which provide more flexibility to reduce the number of triggered events than the existing results on linear MASs. The protocol with adaptive coupling is of the fully distributed nature. It is proved that the proposed protocols can ensure consensus and are not Zeno. A numerical example is provided to illustrate the effectiveness and advantages of the designed protocols.

关键词： Multi-agent systems Consensus Dynamic event-triggered(DET) protocol Adaptive coupling

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A Knowledge Base System for Operation optimization: Design and Implementation Practice for the Polyethylene Process

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Engineering 2019年第6期5卷 1041-1048页

作者： Weimin Zhong Chaoyuan Li Xin Peng Feng Wan Xufeng An Zhou Tian Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and TechnologyShanghai 200237China

Setting up a knowledge base is a helpful way to optimize the operation of the polyethylene process by improving the performance and the ef ciency of reuse of information and knowledge two critical ele- ments in polyethylene smart manufacturing. In this paper, we propose an overall structure for a knowl- edge base based on practical customer demand and the mechanism of the polyethylene process. First, an ontology of the polyethylene process constructed using the seven-step method is introduced as a carrier for knowledge representation and sharing. Next, a prediction method is presented for the molecular weight distribution (MWD) based on a back propagation (BP) neural network model, by analyzing the relationships between the operating conditions and the parameters of the MWD. Based on this network, a differential evolution algorithm is introduced to optimize the operating conditions by tuning the MWD. Finally, utilizing a MySQL database and the Java programming language, a knowledge base system for the operation optimization of the polyethylene process based on a browser/server framework is realized.

关键词： Ontology Operation optimization Knowledge base system Polyethylene process

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Cost-Quality Adaptive Active Learning for Chinese Clinical Named Entity Recognition

Cost-Quality Adaptive Active Learning for Chinese Clinical N...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Tingting Cai Yangming Zhou Hong Zheng School of Information Science and Engineering East China University of Science and Technology Shanghai China Ministry of Education Key Laboratory of Advanced Control and Optimization for Chemical Processes China

ISBN: (数字)9781728162157

ISBN: (纸本)9781728162164

Clinical Named Entity Recognition (CNER) aims to automatically identity clinical terminologies in Electronic Health Records (EHRs), which is a fundamental and crucial step for clinical research. To train a high-performance model for CNER, it usually requires a large number of EHRs with high-quality labels. However, labeling EHRs, especially Chinese EHRs, is time-consuming and expensive. One effective solution to this issue is active learning, where a model asks labelers to annotate data which is beneficial to model performance improvement. Conventional active learning assumes a single labeler that always replies noiseless answers to queried labels. However, in real settings, multiple labelers provide diverse quality of annotation with varied cost and labelers with low overall annotation quality can still assign correct labels for some specific instances. In this paper, we propose a Cost-Quality Adaptive Active Learning (CQAAL) approach for CNER in Chinese EHRs, which maintains a balance between the annotation quality, labeling cost and the informativeness of selected instances. Specifically, our proposed CQAAL method selects cost-effective instance-labeler pairs to achieve better annotation quality with lower cost in an adaptive manner. Computational results on the CCKS2017 dataset demonstrate the superiority and effectiveness of CQAAL.

关键词： Annotations Uncertainty Labeling Task analysis Entropy Manuals Neural networks

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Quasi-Synchronization of Heterogeneous Lur'e Networks With Impulsive Feedback control

Quasi-Synchronization of Heterogeneous Lur'e Networks With I...

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第40届中国控制会议

作者： Chongfang Jin Sangli Shi Zhengxin Wang Wangli He Guo-Ping Jiang School of Science Nanjing University of Posts and Telecommunications Jiangsu Engineering Lab for IOT Intelligent Robots (IOTRobot) Nanjing University of Posts and Telecommunications The Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and Technology School of Automation Nanjing University of Posts and Telecommunications

The target of this paper is studying the quasi-synchronization problems of the heterogeneous Lur'e networks with impulsive feedback control. By introducing impulsive feedback control, the heterogeneous Lur'e network is analyzed. The sufficient condition for guaranteeing quasi-synchronization is derived by means of linear matrix inequality(LMI), the Schur complement and the principle of comparison. More over, the upper bound of exponential quasi-synchronization errors is further calculated. Finally, the numerical simulations are presented to illustrate the effectiveness of the control protocol and theoretical results.

关键词： Exponential quasi-synchronization Lur'e network Feedback Impulsive control

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A Dynamic Event-Triggered Approach to Multi-Agent Consensus

A Dynamic Event-Triggered Approach to Multi-Agent Consensus

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Chinese control Conference (CCC)

作者： Xianwei Li Yang Tang Shaoyuan Li Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

This paper focuses on designing dynamic event-triggered (DET) protocols for consensus control of general linear multi-agent systems (MASs). Design algorithms are constructed for DET protocols with static and adaptive coupling, respectively. The designed event-triggering conditions involve internal dynamic variables that depend on the error information of the system, which provide more flexibility to reduce the number of triggered events than the existing results on linear MASs. The protocol with adaptive coupling is of the fully distributed nature. It is proved that the proposed protocols can ensure consensus and are not Zeno. A numerical example is provided to illustrate the effectiveness and advantages of the designed protocols.

关键词： Protocols Couplings Laplace equations Multi-agent systems Lyapunov methods Closed loop systems optimization

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Cost-quality adaptive active learning for chinese clinical named entity recognition

arXiv

引用

arXiv 2020年

作者： Cai, Tingting Zhou, Yangming Zheng, Hong School of Information Science and Engineering East China University of Science and Technology Shanghai200237 China Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education China

Clinical Named Entity Recognition (CNER) aims to automatically identity clinical terminologies in Electronic Health Records (EHRs), which is a fundamental and crucial step for clinical research. To train a high-performance model for CNER, it usually requires a large number of EHRs with high-quality labels. However, labeling EHRs, especially Chinese EHRs, is time-consuming and expensive. One effective solution to this is active learning, where a model asks labelers to annotate data which the model is uncertain of. Conventional active learning assumes a single labeler that always replies noiseless answers to queried labels. However, in real settings, multiple labelers provide diverse quality of annotation with varied costs and labelers with low overall annotation quality can still assign correct labels for some specific instances. In this paper, we propose a Cost-Quality Adaptive Active Learning (CQAAL) approach for CNER in Chinese EHRs, which maintains a balance between the annotation quality, labeling costs, and the informativeness of selected instances. Specifically, CQAAL selects cost-effective instance-labeler pairs to achieve better annotation quality with lower costs in an adaptive manner. Computational results on the CCKS-2017 Task 2 benchmark dataset demonstrate the superiority and effectiveness of the proposed CQAAL. Copyright © 2020, The Authors. All rights reserved.

关键词： Records management

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Delay-dependent output feedback integral sliding mode control of singularly perturbed systems

Delay-dependent output feedback integral sliding mode contro...

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International Conference on control and Automation (ICCA)

作者： Jing Xu Yugang Niu Key Laboratory of Advanced Control and Optimization for Chemical Process East China University of Science and Technology Shanghai China

ISBN: (数字)9781728190938

ISBN: (纸本)9781728190945

This paper presents a descriptor system method for output feedback integral sliding mode control of singularly perturbed systems. The fast state, representing the derivative of output, is approximated with aid of an artificial time-delay estimator. Then, a delay-dependent integral sliding mode controller is designed to ensure the occurrence of sliding phase since the initial time instant. The finite frequency uncertainty is divided into the matched and uncertainty uncertainty. On this basis, the proposed controller contains the nominal part to attain the robustness to the unmatched uncertainty, and the switching part to compensate the matched uncertainty. Finally, the effectiveness of the design method is verified in a mass-damper-spring system subject to finite frequency perturbations.

关键词： Uncertainty Output feedback Perturbation methods Sliding mode control Linear matrix inequalities Delay effects Matrix decomposition

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Data-driven Scheduling optimization of Ethylene Cracking Furnace System

Data-driven Scheduling Optimization of Ethylene Cracking Fur...

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第32届中国控制与决策会议

作者： Xinwei Lin Liang Zhao Wenli Du Feng Qian Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology

The ethylene cracking furnace system convert a variety of hydrocarbon feeds into products such as ethylene and propylene in parallel. During the cracking process, the coke produced by the cracking will degrade the performance of the cracking furnace, so the furnace should be cleaned periodically. Scheduling of the cracking furnace system involves various raw materials, multiple furnaces, and multiple constraints, so it is a difficult mathematic programming problem. Previous studies have simplified the optimization model to obtain a corresponding mixed integer nonlinear programming（MINLP） model. In order to make the scheduling more suitable for the actual process, this paper develops the transfer-line exchanger（TLE） model, fuel consumption model, and super-high pressure steam（SS） model by using the actual plant data. A case study is put forward to demonstrate the effectiveness of the proposed method.

关键词： Ethylene cracking furnace system scheduling MINLP TLE

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Almost Sure Exponential Stability of Altafini Model with Multiplicative Noise for Opinion Dynamics

Almost Sure Exponential Stability of Altafini Model with Mul...

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第三十九届中国控制会议

作者： Fanli Yuan Ying Cui Haili Liang Zhao Zhou Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and AutomationShanghai University Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and Technology

In this paper, we investigate the stability analysis of stochastic opinion dynamics in which the agents are interfered by multiplicative noise. We propose a stochastic Altafini model of opinion evolution in signed social networks with multiplicative noise and give the analysis of almost sure exponential stability(ASES). Compared with the deterministic opinion dynamic and stochastic opinion dynamics in additive noise environments, our results concern the effects of the agents' free will, i.e.,multiplicative noise, in signed social networks. We establish a sufficient condition with stochastic multiplicative noise which can guarantee the stochastic system is almost sure exponential stability(ASES) when the parameters of the strength of noise is limited by the conditions. Numerical simulations are given to illustrate the above theoretical results.

关键词： Signed Networks Opinion Dynamics Stability Stochastic Systems

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A federated data-driven evolutionary algorithm

arXiv

引用

arXiv 2021年

作者： Xu, Jinjin Jin, Yaochu Du, Wenli Gu, Sai Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China Department of Computer Science University of Surrey GuildfordGU2 7XH United Kingdom Department of Chemical and Process Engineering University of Surrey GuildfordGU27XH United Kingdom

Data-driven evolutionary optimization has witnessed great success in solving complex real-world optimization problems. However, existing data-driven optimization algorithms require that all data are centrally stored, which is not always practical and may be vulnerable to privacy leakage and security threats if the data must be collected from different devices. To address the above issue, this paper proposes a federated data-driven evolutionary optimization framework that is able to perform data driven optimization when the data is distributed on multiple devices. On the basis of federated learning, a sorted model aggregation method is developed for aggregating local surrogates based on radial-basis-function networks. In addition, a federated surrogate management strategy is suggested by designing an acquisition function that takes into account the information of both the global and local surrogate models. Empirical studies on a set of widely used benchmark functions in the presence of various data distributions demonstrate the effectiveness of the proposed framework. © 2021, CC BY.

关键词： optimization

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