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IEEE/CAA Journal of Automatica Sinica 2017年第1期4卷 1-5页

作者： Fei-Yue Wang Jie Zhang Qinglai Wei Xinhu Zheng Li Li IEEE State Key Laboratory of Management and Control for Complex Systems(SKL-MCCS) Institute of AutomationChinese Academy of Sciences(CASIA) School of Computer and Control Engineering University of Chinese Academy of Sciences Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences(SKL-MCCSCASIA) Qingdao Academy of Intelligent Industries Department of Computer Science and Engineering University of Minnesota Department of Automation Tsinghua University

Deep reinforcement learning is a focus research area in artificial intelligence. The principle of optimality in dynamic programming is a key to the success of reinforcement learning methods. The principle of adaptive dynamic programming ADP is first presented instead of direct dynamic programming DP , and the inherent relationship between ADP and deep reinforcement learning is developed. Next, analytics intelligence, as the necessary requirement, for the real reinforcement learning, is discussed. Finally, the principle of the parallel dynamic programming, which integrates dynamic programming and analytics intelligence, is presented as the future computational intelligence. © 2014 Chinese Association of automation.

关键词： Artificial intelligence Neural networks Reinforcement learning

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Transforming heat transfer with thermal metamaterials and devices

arXiv

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arXiv 2020年

作者： Li, Ying Li, Wei Han, Tiancheng Zheng, Xu Li, Jiaxin Li, Baowen Fan, Shanhui Qiu, Cheng-Wei Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China ZJU-Hangzhou Global Science and Technology Innovation Center Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Zhejiang University Hangzhou310027 China Department of Electrical Engineering Ginzton Laboratory Stanford University StanfordCA94305 United States National Engineering Research Center of Electromagnetic Radiation Control Materials State Key Laboratory of Electronic Thin Film and Integrated Devices University of Electronic Science and Technology of China Chengdu610054 China Department of Physics University of Colorado BoulderCO80309 United States School of Mechatronics Engineering Harbin Institute of Technology Harbin150001 China Paul M. Rady Department of Mechanical Engineering University of Colorado BoulderCO80309 United States

| The demand for sophisticated tools and approaches in heat management and control has triggered fast development of emerging fields including conductive thermal metamaterials, nanophononics, far-field and near-field radiative thermal management, etc. In this review, we cast a unified perspective on the control of heat transfer, based on which the related studies can be considered as complementary paradigms toward manipulating physical parameters and realizing unprecedented phenomena in heat transfer using artificial structures, such as thermal conductivity in heat conduction, thermal emissivity in radiation, and properties related to multi-physical effects. The review is divided into three parts that focus on the three main categories of heat flow control, respectively. Thermal conduction and radiation are emphasized in the first and second parts at both macro- and micro-scale. The third part discusses the efforts to actively introduce heat sources or tune the material parameters with multi-physical effects in both conduction and radiation, including works using thermal convection. We conclude the review with challenges in this research topic and new possibilities about topological thermal effects, heat waves, and quantum thermal effects. Copyright © 2020, The Authors. All rights reserved.

关键词： Metamaterials

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Generative Adversarial Networks:Introduction and Outlook

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IEEE/CAA Journal of Automatica Sinica 2017年第4期4卷 588-598页

作者： Kunfeng Wang Chao Gou Yanjie Duan Yilun Lin Xinhu Zheng Fei-Yue Wang IEEE State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Qingdao Academy of Intelligent Industries State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences University of Chinese Academy of Sciences Department of Computer Science and Engineering University of Minnesota Research Center for Computational Experiments and Parallel Systems Technology National University of Defense Technology

Recently, generative adversarial networks(GANs)have become a research focus of artificial intelligence. Inspired by two-player zero-sum game, GANs comprise a generator and a discriminator, both trained under the adversarial learning *** goal of GANs is to estimate the potential distribution of real data samples and generate new samples from that *** their initiation, GANs have been widely studied due to their enormous prospect for applications, including image and vision computing, speech and language processing, etc. In this review paper, we summarize the state of the art of GANs and look into the future. Firstly, we survey GANs' proposal background,theoretic and implementation models, and application ***, we discuss GANs' advantages and disadvantages, and their development trends. In particular, we investigate the relation between GANs and parallel intelligence,with the conclusion that GANs have a great potential in parallel systems research in terms of virtual-real interaction and integration. Clearly, GANs can provide substantial algorithmic support for parallel intelligence.

关键词： ACP approach adversarial learning generative adversarial networks(GANs) generative models parallel intelligence zero-sum game

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The learning of fuzzy cognitive maps with noisy data: A rapid and robust learning method with maximum entropy

arXiv

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arXiv 2019年

作者： Feng, Guoliang Lu, Wei Pedrycz, Witold Yang, Jianhua Liu, Xiaodong School of Control Science and Engineering Dalian University of Technology Dalian116023 China School of Automation Engineering Northeast Electric Power University Jilin132012 China School of Control Science and Engineering Dalian University of Technology Dalian116023 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia

Numerous learning methods for fuzzy cognitive maps (FCMs), such as the Hebbian-based and the population-based learning methods, have been developed for modeling and simulating dynamic systems. However, these methods are faced with several obvious limitations. Most of these models are extremely time consuming when learning the large-scale FCMs with hundreds of nodes. Furthermore, the FCMs learned by those algorithms lack robustness when the experimental data contain noise. In addition, reasonable distribution of the weights is rarely considered in these algorithms, which could result in the reduction of the performance of the resulting FCM. In this article, a straightforward, rapid, and robust learning method is proposed to learn FCMs from noisy data, especially, to learn large-scale FCMs. The crux of the proposed algorithm is to equivalently transform the learning problem of FCMs to a classic-constrained convex optimization problem in which the least-squares term ensures the robustness of the well-learned FCM and the maximum entropy term regularizes the distribution of the weights of the well-learned FCM. A series of experiments covering two frequently used activation functions (the sigmoid and hyperbolic tangent functions) are performed on both synthetic datasets with noise and real-world datasets. The experimental results show that the proposed method is rapid and robust against data containing noise and that the well-learned weights have better distribution. In addition, the FCMs learned by the proposed method also exhibit superior performance in comparison with the existing methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Fuzzy rules

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Reinforcement Learning-Based Predictive control for Autonomous Electrified Vehicles

Reinforcement Learning-Based Predictive Control for Autonomo...

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2018 IEEE Intelligent Vehicles Symposium, IV 2018

作者： Liu, Teng Yang, Chao Hu, Chuanzheng Wang, Hong Li, Li Cao, Dongpu Wang, Fei-Yue State Key Laboratory of Automotive Simulation and Control Jilin University China Vehicle Intelligence Pioneers Inc. Qingdao Shandong266109 China Jiangsu XCMG Construction Machinery Research Institute Ltd. Xuzhou Jiangsu221004 China Mechanical and Mechatronics Engineering Department Waterloo University N2L 3G1 Canada Faculty of Department of Automation Tsinghua University China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781538644522

This paper proposes a learning-based predictive control technique for self-driving hybrid electric vehicle (HEV). This approach is a hierarchical framework. The higher-level is a human-like driver model, which is applied to predict accelerations in the car following situation to replicate a human driver's demonstrations. The lower-level is a reinforcement learning (RL)-based controller, which enforces the battery and fuel consumption constraints to improve energy efficiency of HEV. In addition, we present induced matrix norm (IMN) to handle cases that the training data cannot provide sufficient information on how to operate in current driving situation. Simulation results illustrate that the proposed method can reproduce human driver's driving style and promote fuel economy. © 2018 IEEE.

关键词： Reinforcement learning

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Nonlinear optimal control for ship propulsion with the use of an induction motor and a drivetrain 5

Nonlinear optimal control for ship propulsion with the use o...

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5th International Conference of engineering Against Failure, ICEAF-V 2018

作者： Rigatos, Gerasimos Busawon, Krishna Serpanos, Dimitrios Siadimas, Vasilios Siano, Pierluigi Abbaszadeh, Masoud Unit of Industrial Automation Industrial Systems Institute Rion Patras26504 Greece Nonlinear Control Group University of Northumbria NewcastleNE1 8ST United Kingdom Industrial Systems Institute RC Athena Rion Patras26504 Greece Department of Electrical and Computer Engineering University of Patras Rion Patras26504 Greece Department of Industrial Engineering University of Salerno Fisciano84084 Italy GE Global Research General Elecric NiskayunaNY12309 United States

A nonlinear optimal (H-infinity) control method is proposed for an electric ship's propulsion system that consists of an induction motor, a drivetrain and a propeller. The control method relies on approximate linearization of the propulsion system's dynamic model using Taylor-series expansion and on the computation of the state-space description's Jacobian matrices. The linearization takes place around a temporary equilibrium which is recomputed at each time-step of the control method. For the approximately linearized model of the ship's propulsion system, an H-infinity (optimal) feedback controller is developed. For the computation of the controller's gains an algebraic Riccati equation is solved at each iteration of the control *** stability properties of the control method are proven through Lyapunov analysis, © The Authors, published by EDP Sciences, 2018.

关键词： Linearization

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Condition monitoring for the quadruple water tank system using H-infinity Kalman Filtering 5

Condition monitoring for the quadruple water tank system usi...

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5th International Conference of engineering Against Failure, ICEAF-V 2018

作者： Rigatos, Gerasimos Serpanos, Dimitrios Siadimas, Vasilios Busawon, Krishna Gao, Zhiwei Siano, Pierluigi Abbaszadeh, Masoud Unit of Industrial Automation Industrial Systems Institute Rion Patras26504 Greece Industrial Systems Institute RC Athena Rion Patras26504 Greece Department of Electrical and Computer Engineering University of Patras Rion Patras26504 Greece Nonlinear Control Group University of Northumbria NewcastleNE1 8ST United Kingdom Department of Industrial Engineering University of Salerno Fisciano84084 Italy GE Global Research General Elecric NiskayunaNY12309 United States

The problem of statistical fault diagnosis for the quadruple watertanks system is examined. The solution of the fault diagnosis problem for the dynamic model of the four-water tanks system is a non-trivial case, due to nonlinearities and the system's multivariable structure. In the article's approach, the system's dynamic model undergoes first approximate linearization around a temporary operating point which is recomputed at each sampling period. The linearization procedure relies on Taylor series expansion and on the computation of the Jacobian matrices of the state-space description of the system. The H-infinity Kalman Filter is used as a robust state estimator for the approximately linearized model of the quadruple water tanks system. By comparing the outputs of the H-infinity Kalman Filter against the outputs measured from the real water tanks system the residuals sequence is generated. It is concluded that the sum of the squares of the residuals' vectors, being weighted by the inverse of the associated covariance matrix, stands for a stochastic variable that follows the χ2 distribution. As a consequence, a statistical method for condition monitoring of the quadruple water tanks system is drawn, by using the properties of the χ2 distribution and the related confidence intervals. Actually, normal functioning can be ensured as long as the value of the aforementioned stochastic variable stays within the previously noted confidence intervals. On the other side, one can infer the malfunctioning of the quadruple water tanks system with a high level of certainty (e.g. of the order of 96% to 98%), when these confidence intervals are exceeded. The article's method allows also for fault isolation, that is for identifying the specific component of the quadruple water tanks system that has been subject to fault or cyber-attack. © The Authors, published by EDP Sciences, 2018.

关键词： Water tanks

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Modeling and Simulation of Virtual Synchronous Generator for DFIG wind turbine generator

Modeling and Simulation of Virtual Synchronous Generator for...

引用

International Conference on Renewable Power Generation

作者： Qiongfeng Zhu Ziyu Chen Shouhong Feng Yufeng Wang Bowen Zhang Weilin Li State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems (China Electric Power Research Institute) Beijing China Department of Electrical Engineering School of Automation Northwestern Polytechnical University Xi'an China

ISBN: (数字)9781839531248

ISBN: (纸本)9781839531255

With the rapid development of the wind power generation, the penetration rate of wind power is gradually increasing, which affects the stable operation of the power system. The DFIG wind turbine generator can realize decoupling control of output active and reactive power by vector transformation control. However, under this power control, wind turbines do not have the electromechanical transient characteristics like synchronous generators for supporting the stable operation of the power system. Virtual synchronous generator technology can make the wind power system reflect the operation mechanism and external characteristics of traditional synchronous generators to improve the stability of power system. This paper builds a generic simulation model of current source type DFIG wind turbine generator based on VSG technology, which can simulate a series of VSG behaviors including virtual inertia control, damping control, primary frequency control, reactive power control and fault ride through. The developed simulation model is also validated comparing to the actual wind turbine field testing data, which shows accurate and reliable simulation results. The developed simulation model can provide theoretical and model basis for studying VSG technology and grid integration characteristics.

关键词： MICROGRID VSG DOUBLY-FED WIND GENERATOR DROOP control

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Wireless Monitoring, control and automation in Pulp and Paper Industry 14

Wireless Monitoring, Control and Automation in Pulp and Pape...

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14th IEEE India Council International Conference, INDICON 2017

作者： Jayasri, S.P. Vyshnavi, N. Moorthi, S. Department of Instrumentation and Control Engineering National Institute of Technology Tiruchirappalli620015 India Department of EEE VLSI Systems Research Lab National Institute of Technology Tiruchirappalli620015 India

ISBN: (纸本)9781538643181

This paper describes wireless control and automation of various processes in paper mills using CC3200. Embedded web server is preferred over PC server in case of internet applications based on client/server architecture for its decreasing size, cost and power consumption. CC3200 has an exclusive feature of low power consumption which makes it convenient for use in industries. A user-friendly webpage interface nodered is introduced to the users and system administrators to locally (LAN) or remotely (internet) manage and control the processes. Email alerts are sent to the users in case of faults and intelligent algorithms can be implemented to rectify the faults which improves the efficiency of the system. © 2017 IEEE.

关键词： Electric power utilization

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Optimal DoS Attack Strategy against Remote State Estimation Over Lossy Networks 29

Optimal DoS Attack Strategy against Remote State Estimation ...

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第29届中国控制与决策会议

作者： Menglin Li Jiahu Qin Ling Shi Xinghuo Yu Huijun Gao Department of Automation University of Science and Technology of China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology School of Engineering RMIT University Research Institute of Intelhgent Control and Systems Harbin Institute of Technology

ISBN: (纸本)9781509046584

This paper considers a Denial-of-Service(DoS) attack scheduling ***,a sensor employs the wireless fink to send the data packet to the remote estimator at each time step,while an energy-constrained attacker launches DoS attacks against the remote state estimation,and designs an optimal attack strategy to maximize damage to the remote estimation *** packet will drop if the channel is *** most of the existing works on DoS attacks,it is assumed that the wireless channel is perfect,i.e.,the packet dropout never occurs in the absence of ***,this is far from the practical *** encompass the lossy nature of wireless networks,we study the scenario of lossy networks in which the packet may drop even without attack,and construct the optimal attack strategy that maximizes the average expected estimation error at the remote estimator over lossy *** simulations are provided to demonstrate the effectiveness of the theoretical results.

关键词： Cyber-Physical systems DoS attack lossy networks energy constraint remote state estimation

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