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Robust Semi-Global Leaderless Consensus and Containment control of Identical Linear Systems with Imperfect Actuators

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Journal of Systems Science & Complexity 2018年第1期31卷 69-86页

作者： SHI Liangren ZHAO Zhiyun LIN Zongli Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai 200240 China Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology) Ministry of Education Shanghai 200237 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743 Charlottesville VA 22904-4743 USA

This paper investigates both the robust semi-global leaderless consensus problem and the robust semi-global containment control problem for a group of identical linear systems with imperfect actuators. The imperfect actuators are characterized by nonlinearities such as saturation and dead zone and there input output relationships are not precisely known. The dynamics of follower agents are also affected by the input additive disturbances. Low-and-high gain feedback consensus protocols are constructed to solve these problems. More specifically, it is shown that robust semi-global leaderless consensus can be achieved over a connected undirected graph and robust semi-global containment control can be achieved when each follower agent has access to the information of at least one leader agent. Numerical simulation illustrates the theoretical results.

关键词： Consensus containment control dead zone leaderless consensus multi-agent systems saturation

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When autonomous systems meet accuracy and transferability through AI: A survey

arXiv

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arXiv 2020年

作者： Zhang, Chongzhen Wang, Jianrui Yen, Gary G. Zhao, Chaoqiang Sun, Qiyu Tang, Yang Qian, Feng Kurths, Jürgen Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China School of Electrical and Computer Engineering Oklahoma State University StillwaterOK74075 United States Potsdam Institute for Climate Impact Research Potsdam14473 Germany Institute of Physics Humboldt University of Berlin Berlin12489 Germany

With widespread applications of artificial intelligence (AI), the capabilities of the perception, understanding, decision-making and control for autonomous systems have improved significantly in the past years. When autonomous systems consider the performance of accuracy and transferability, several AI methods, like adversarial learning, reinforcement learning (RL) and meta-learning, show their powerful performance. Here, we review the learning-based approaches in autonomous systems from the perspectives of accuracy and transferability. Accuracy means that a well-trained model shows good results during the testing phase, in which the testing set shares a same task or a data distribution with the training set. Transferability means that when a well-trained model is transferred to other testing domains, the accuracy is still good. Firstly, we introduce some basic concepts of transfer learning and then present some preliminaries of adversarial learning, RL and meta-learning. Secondly, we focus on reviewing the accuracy or transferability or both of them to show the advantages of adversarial learning, like generative adversarial networks (GANs), in typical computer vision tasks in autonomous systems, including image style transfer, image super-resolution, image deblurring/dehazing/rain removal, semantic segmentation, depth estimation, pedestrian detection and person re-identification (re-ID). Then, we further review the performance of RL and meta-learning from the aspects of accuracy or transferability or both of them in autonomous systems, involving pedestrian tracking, robot navigation and robotic manipulation. Finally, we discuss several challenges and future topics for using adversarial learning, RL and meta-learning in autonomous systems. Copyright © 2020, The Authors. All rights reserved.

关键词： Reinforcement learning

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Sliding Mode control for Networked control System Under Fading Channels

Sliding Mode Control for Networked Control System Under Fadi...

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control Technology and Applications (CCTA),

作者： Jiarui Li Yugang Niu Yuanyuan Zou Key Laboratory of Advanced Control and optimization for Chemical Process (East China University of Science and Technology) Ministry of Education Shanghai China Department of Automation Shanghai Jiao Tong University Shanghai China

In this work, the discrete-time sliding mode control problem for the networked control systems under fading channels is investigated. Moreover, the state signals will be quantized through a logarithmic quantizer before transmitted to the controller. Subsequently, a sliding surface relating to fading coefficient is designed to cope with the fading measurements. It is shown that the designed sliding mode controller can drive the state trajectories into the neighborhood of the specified sliding surface and the closed-loop system is asymptotically stable in the sense of mean square. In the end, a numerical simulation is given.

关键词： Fading channels Quantization (signal) Symmetric matrices Sliding mode control Closed loop systems Lyapunov methods Networked control systems

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Sliding Mode control of State-Saturated Systems Under Dynamic Event-Triggered Protocol

Sliding Mode Control of State-Saturated Systems Under Dynami...

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Asian control Conference

作者： Jun Song Yugang Niu Bei Chen The Key Laboratory of Advanced Control and Optimization for Chemical Process East China University of Science and Technology Shanghai China School of Electric and Electronic Engineering Shanghai University of Engineering Science Shanghai China

ISBN: (纸本)9781728102634

This paper endeavors to investigate the sliding mode control (SMC) issue of the networked state-saturated systems. For the energy saving purpose in network communication, a dynamic event-triggering mechanism is employed to SMC design by introducing interval dynamic variable. With the aid of some appropriate Lyapunov functionals, the sufficient conditions are derived to ensure the asymptotic stability of the sliding mode dynamics and the reachability of the specified sliding surface. Moreover, a convex optimization algorithm is formulated to solve the dynamic event-triggering SMC law. Finally, a numerical example is provided to illustrate the effectiveness of the proposed results.

关键词： Zirconium Heuristic algorithms Symmetric matrices Sliding mode control Asymptotic stability Protocols Nonlinear dynamical systems

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A Computer-Aided Tuning Method for Microwave Filters by Combing T-S Fuzzy Neural Networks and Improved Space Mapping

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Computer Modeling in Engineering & Sciences 2018年第9期116卷 433-453页

作者： Shengbiao Wu Weihua Cao Can Liu Min Wu School of Automation China University of GeoscienceWuhanHubei430074China Nanchang Institute of Science and Technology.Nanchang Jiangxi330100China The Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems WuhanHubei430074China

A computer-aided tuning method that combines T-S fuzzy neural network(TS FNN)and offers improved space mapping(SM)is presented in this *** method consists of three main ***,the coupling matrix is effectively extracted under the influence of phase shift and cavity loss after the initial ***,the surrogate model is realized by using a T-S FNN based on subspace ***,the mapping relationship between the actual and the surrogate models is established by the improved space mapping algorithm,and the optimal position of the tuning screws are found by updating the input and output parameters of the surrogate ***,the effectiveness of different methods is verified by an experiment with a nine order cross coupled *** results show that,compared to a back propagation neural network method based on electromagnetic simulation and an SM method based on a least squares support vector machine,the proposed method has obvious advantages in terms of tuning accuracy and tuning time.

关键词： Computer-aided tuning T-S FNN S-parameters coupling matrix

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Ternary Compression for Communication-Efficient Federated Learning

arXiv

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arXiv 2020年

作者： Xu, Jinjin Du, Wenli Jin, Yaochu He, Wangli Cheng, Ran The Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai200092 China The Department of Computer Science University of Surrey GuildfordGU2 7XH United Kingdom Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China

Learning over massive data stored in different locations is essential in many real-world applications. However, sharing data is full of challenges due to the increasing demands of privacy and security with the growing use of smart mobile devices and IoT devices. Federated learning provides a potential solution to privacy-preserving and secure machine learning, by means of jointly training a global model without uploading data distributed on multiple devices to a central server. However, most existing work on federated learning adopts machine learning models with full-precision weights, and almost all these models contain a large number of redundant parameters that do not need to be transmitted to the server, consuming an excessive amount of communication costs. To address this issue, we propose a federated trained ternary quantization (FTTQ) algorithm, which optimizes the quantized networks on the clients through a self-learning quantization factor. Theoretical proofs of the convergence of quantization factors, unbiasedness of FTTQ, as well as a reduced weight divergence are given. On the basis of FTTQ, we propose a ternary federated averaging protocol (T-FedAvg) to reduce the upstream and downstream communication of federated learning systems. Empirical experiments are conducted to train widely used deep learning models on publicly available datasets, and our results demonstrate that the proposed T-FedAvg is effective in reducing communication costs and can even achieve slightly better performance on non-IID data in contrast to the canonical federated learning algorithms. Copyright © 2020, The Authors. All rights reserved.

关键词： Learning algorithms

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Security of opinion dynamics in social networks ⁎

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IFAC-PapersOnLine 2019年第3期52卷 162-167页

作者： Long Gao Wen Yang Zhiyun Zhao Xiaofan Wang Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai China 200237 Department of Automation Shanghai Jiaotong University Shanghai China 200240 School of Mechatronic Engineering and Automation Shanghai University Shanghai China 200072

In this paper, we consider the security problem of opinion dynamics in attack-defense environment in social networks. First, we propose an opinion dynamics model, which is composed by attackers, defenders and the masses. In the proposed model, a set of attackers controlled by the agent with hostile opinion sends malicious opinion to their neighbors with a certain probability, and the defenders are activated by the agent with right opinion at a triggering time to lead the opinions of the masses to a safe zone. Second, we provide a sufficient condition to ensure the convergence of the expected opinions of the system. We also give the method to seek a lower bound of the opinions spread by the defenders at each time step while keeping the opinions in safe situation. Finally, we provide a numerical example to verify the main results.

关键词： Opinion dynamic attack-defense environment network security social network

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Dynamic optimization of Chemical Processes using Symbiotic Organisms Search Algorithm

Dynamic Optimization of Chemical Processes using Symbiotic O...

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Chinese Automation Congress (CAC)

作者： Peng Tian Xu Chen Wenxiang Zhao Wenli Du School of Electrical and Information Engineering Jiangsu University Zhenjiang Jiangsu China Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai China

Chemical process optimization problems are often modeled as dynamic optimization problems (DOPs). Due to the nonlinear, multimodal and multi-dimensional nature of DOPs, efficient solution of DOPs is a very challenging task. In this paper, a new intelligent search algorithm called symbiotic organisms search (SOS) is proposed for tackling the chemical DOPs. SOS mainly mimics three symbiotic relationships in ecosystem, namely mutualism, commensalism and parasitism, to perform global search. In addition, compared with previous intelligent search algorithms, SOS has the advantages of no tuning parameters, easy to implement and high performance. Combined with control vector parameterization, the proposed SOS is applied to solve five chemical DOPs with different levels of complexity. Simulation results show that SOS can achieve solutions with accuracy comparable to those methods in the literature, and thus can be regarded as an effective tool for the chemical DOPs.

关键词： optimization Heuristic algorithms Chemicals Symbiosis Sociology Statistics Organisms

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Predictive control for Continuous Stirred Tank Reactors

Predictive Control for Continuous Stirred Tank Reactors

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2019 International Conference on Informatics, control and Robotics 2019信息学、控制和机器人学国际会议(ICICR2019)

作者： Ioana NASCU Ioan NASCU Wen-li DU Sai GU Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Department of Chemical and Process Engineering University of Surrey Department of Automation Technical University of Cluj-Napoca

The paper focuses on the implementation of a model based predictive control(MBPC) method, for Continuous Stirred Tank Reactors. First, the modelling problem of a single irreversible exothermic reaction, taking place in a perfectly mixed continuously stirred tank reactor(CSTR) is presented. The dynamic model consists of differential material and energy balance equations. The control strategy is investigated and evaluated by performing simulations and analyzing the results. The disturbance rejection capacity of the control system(regulatory control performances) have been tested and compared with those obtained using a classical Proportional Integral Derivative(PID) based controller. The results show that this control strategy has good performances and can be efficiently used to control the CSTR.

关键词： Predictive control PID control Chemical reactor Process model

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流程工业制造系统智能化——人工智能与流程制造深度融合

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Engineering 2019年第6期 980-981页

作者：钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology

近年来,流程工业制造系统智能化得到了国内外学术界和工业界的高度关注和重视。各国政府联合学术界、工业界纷纷推出了智能制造的战略计划,其主要理念是在工业物联网基础上"通过融合知识的企业级资源计划优化、调度优化和生产过程... 详细信息

近年来,流程工业制造系统智能化得到了国内外学术界和工业界的高度关注和重视。各国政府联合学术界、工业界纷纷推出了智能制造的战略计划,其主要理念是在工业物联网基础上"通过融合知识的企业级资源计划优化、调度优化和生产过程优化实现过程工业的升级转型"。然而,

关键词：人工智能流程制造流程工业深度融合

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