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Parallel Reinforcement Learning:A Framework and Case Study

IEEE/CAA Journal of Automatica Sinica 2018年第4期5卷 827-835页

作者： Teng Liu Bin Tian Yunfeng Ai Li Li Dongpu Cao Fei-Yue Wang State Key Laboratory of Management and Control for Complex System Institute of AutomationChinese Academy of SciencesBeijing 100190China State Key Lab.of Management and Control for Complex System Institute of AutomationChinese Academy of SciencesBeijing 100190China Cloud Computing Center Chinese Academy of SciencesDongguan 523808China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100190China Department of Automation Tsinghua UniversityBeijing 100190China Driver Cognition and Automated Driving Laboratory University of WaterlooWaterloo N2L 3G1Canada IEEE

In this paper, a new machine learning framework is developed for complex system control, called parallel reinforcement learning. To overcome data deficiency of current data-driven algorithms, a parallel system is built to improve complex learning system by self-guidance. Based on the Markov chain(MC) theory, we combine the transfer learning, predictive learning, deep learning and reinforcement learning to tackle the data and action processes and to express the knowledge. Parallel reinforcement learning framework is formulated and several case studies for real-world problems are finally introduced.

关键词： Deep learning machine learning parallel reinforcement learning parallel system predictive learning transfer learning

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Parallel Building Process management system

Parallel Building Process Management System

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Chinese Automation Congress (CAC)

作者： Sheng Liu Xisong Dong Gang Xiong Zhen Shen Bin Hu Xiaoyu Chen State Key Laboratory for Management and Control of Complex System Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Institution of Intelligent Manufacturing Qingdao Academy of Intelligent Industries Qingdao China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665426480

With the development of industrialized building and intelligence technology, it becomes necessary and possible to realize building process intelligence management. In recent years, digital twins and parallel management get more and more attentions in academic research and industrial applications. This paper addresses how parallel building system performs intelligence management on industrialized building process. Firstly, actual building model and artificial building model are created according to actual building system. Then business driving engine and simulation engine drive actual building model and artificial building model, respectively. Participants receive and send messages by software interfaces. Business driving engine changes the status of actual building model and sends the changes to simulation engine. Simulation engine updates the status of artificial building model and runs artificial building model with various parameters. Then it sends the parameter with the best effect to business driving engine. Business driving engine sends recommendations to participants according to the best parameter. Thus, building process intelligence management is achieved.

关键词： Automation Digital twin Buildings User interfaces Software Engines Business

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Defining digital quadruplets in the cyber-physical-social space for parallel driving

arXiv

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arXiv 2020年

作者： Liu, Teng Xing, Yang Chen, Long Cao, Dongpu Wang, Fei-Yue Vehicle Intelligence Pioneers Inc Shandong Qingdao266109 China Qingdao Academy of Intelligent Industries QingdaoShandong266109 China Department of Mechanical and Mechatronics Engineering University of Waterloo N2L 3G1 Canada State Key Laboratory of Management and Control for Complex System Institute of Automation Beijing China

Parallel driving is a novel framework to synthesize the vehicle intelligence and transport automation. This article aims to define the digital quadruplets in parallel driving. In the cyber-physical-social systems (CPSS), based on the ACP method, the names of the digital quadruplets are first given, which are descriptive, predictive, prescriptive and real vehicles. The objectives of the three virtual digital vehicles are interacting, guiding, simulating and improving with the real vehicles. Then, the three virtual components of the digital quadruplets are introduced in detail and their applications are also illustrated. Finally, the real vehicles in parallel driving system and the research process of the digital quadruplets are depicted. The presented digital quadruplets in parallel driving are expected to make the future connected automated driving safety, efficiently and synergistically. Copyright © 2020, The Authors. All rights reserved.

关键词： Vehicles

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A pigeon-inspired optimization algorithm for many-objective optimization problems

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Science China(Information Sciences) 2019年第7期62卷 131-138页

作者： Zhihua CUI Jiangjiang ZHANG Yechuang WANG Yang CAO Xingjuan CAI Wensheng ZHANG Jinjun CHEN Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology Beijing Institute of Petrochemical Technology Faculty of Information Technology Beijing University of Technology State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences School of Software University of Technology Sydney

Dear editor,Swarm intelligence optimization algorithms are inspired by the behaviour of biological groups in nature. Such algorithms have the advantages of a clear structure, simple operation, comprehensible principles, strong parallelism, effective search abilities, and strong robustness. They can effectively solve difficult problems that traditional methods cannot. Pigeon-inspired optimization (PIO), a novel biomimetic swarm intelligence optimization algorithm, was proposed by Duan and Qiao in

关键词： A pigeon-inspired optimization algorithm for many-objective optimization problems Pareto

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A Vision-Based Path Planning and Following system for a Miniature Robotic Fish

A Vision-Based Path Planning and Following System for a Mini...

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Yue Lu Xingyu Chen Zhengxing Wu Yan Yan Junzhi Yu University of Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China State Key Laboratory for Turbulence and Complex System BIC-ESAT College of Engineering Peking University Beijing China

ISBN: (数字)9781728137261

ISBN: (纸本)9781728137278

Most existing path following algorithms for middle-or large-sized underwater vehicles minimize yaw difference of the control object. Breaking the canonical manner, this paper presents a vision-based path planning and following system for miniature robotic fish. As for path planning, the proposed system finds a gird path based on the AStar algorithm and selects a series of target points in the grid path. By connecting these points in order, a curve path can be planned. In terms of path following, the proposed system forgoes to give a specific yaw and only uses a global camera. It obtains coordinates of the robotic fish in real time by KCF tracking algorithm to calculate an approximate motion vector. A PID controller is employed to drive the difference angle between the motion vector and the target vector (the vector from the robotic fish to the target point) to zero. By swimming to target points one by one, the robotic fish can move to the terminus following the planned path. Finally, aquatic experiments are conducted to verify the effectiveness of the vision-based path planning and following system. The results reveal that the developed system can generate a safe and smooth path, and the robotic fish can follow the path with acceptable deviation.

关键词： Fish Robot kinematics Path planning Robot sensing systems Solenoids Magnetic resonance imaging

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Collaborative Optimization of Cyber Physical Social systems for Urban Transportation Based on Knowledge Automation

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IFAC-PapersOnLine 2020年第5期53卷 572-577页

作者： Gang Xiong Xiaoyu Chen Nan Shuo Yisheng Lv Fenghua Zhu Tianci Qu Peijun Ye State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing 100049 China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing The Cloud Computing Center Chinese Academy of Sciences Dongguan 523808 China Graduate School of System Design Tokyo Metropolitan University Tokyo 191-0065 Japan

The integration of signals from physical, social and cyber spaces, known as Cyber-Physical-Social systems (CPSS), is a new research paradigm for urban transportation, where the traffic control and management (C&M) is collaborative optimized among the three sub-systems. Though some technologies and optimization methods have been studied since its proposition, there is a lack of a systemic architecture as well as an overall implementation about how to efficiently exploit the social signals. For this reason, this paper proposes a general framework of CPSS for urban transportation and presents a feasible solution for traffic optimization based on knowledge automation. The specific implementation includes basic modeling of CPSS, knowledge evolution and reasoning, and collaborative optimization of C&P strategies. As a remarkable highlight, the influence of both individual activities and social learning is concerned during knowledge evolution and reasoning part. A case study from the application in the city of Dongguan is also given to validate our proposed framework and methods, showing that they can efficiently improve the average speed of the actual transportation.

关键词： CPSS knowledge automation urban transportation Collaborative Optimization

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Cyber-Physical-Social systems for Smart City: An Implementation Based on Intelligent Loop

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IFAC-PapersOnLine 2020年第5期53卷 501-506页

Cyber-Physical-Social systems (CPSS) provides a novel perspective for constructing “Smart City”, which is also known as the Human-Machine-Things-system (HMTS), focusing on the fusion of ternary space: social network of human society, network of machines and the Internet of things. In this paper, we propose a specific implementation framework of CPSS for Smart City based on intelligent loops, including basic modeling and interactive fusion, state perception and cognition, and adaptive learning. On this basis, an overall architecture of the CPSS platform is designed, which is applied in the urban transportation management in Hangzhou. The application results demonstrate that the intelligent loop could optimize the control and management strategies for actual urban transportation.

关键词： CPSS Intelligent Loop Human-Cyber-Physical Ternary Space

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Blockchain-based Social Manufacturing for Customization Production

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IFAC-PapersOnLine 2020年第5期53卷 53-58页

作者： Xiuqin Shang Xi Chen Lulu Niu Gang Xiong Zhen Shen Xisong Dong Zhengchao Shen Chao Liu Bangwen Xi the Research Center of Precision Sensing and Control the state key laboratory for management and control of complex systems & Beijing engineering research center of intelligent systems and technology institute of automation Chinese Academy of Sciences Beijing 100190 China Beijing University of Posts and Telecommunications Beijing 100876 China Alstom Beizhong Power (Beijing) Co. Ltd. Beijing 100040 China the System Integration Electronics (Hangzhou)Co. LTD No. 58 No. 11 Road Foxconn Qiantang Tech-Industrial Area HETZ Hangzhou 310018 China

This paper proposes the social manufacturing based on Blockchain, which realizes precise and efficient customization through smart contract and distributed accounting. It is a new manufacturing mode of service-oriented, distributed and collaborative customization. This paper proposes the definition of SM based on Blockchain. In the process of using to Blockchain, it can form a strong trust relationship, so that multiple nodes / roles in SM can save the complete copy of the whole database, rather than a centralized permission / role. Secondly, the Blockchain-based SM system is developed for customized manufacturing. Finally, its application case and the optimization results are given. In SM, it is the key that how to transform customized manufacturing actions into socialized actions of manufacturing resources through internet communities and interconnect Socialized Manufacturing Resources (SMRs) in upstream and downstream. In this paper, the smart contract relationship is established based on Blockchain between SMRs to build credit mechanism in SM, Which can ensure the effective circulation and association of SMRs.

关键词： Social Manufacturing Blockchain Optimization SM Resources

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A decentralized social networking architecture enhanced by blockchain

A decentralized social networking architecture enhanced by b...

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2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Zeng, Shuai Yuan, Yong Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Research Center of Military Computational Experiments and Parallel System National University of Defense Technology Changsha China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781728128535

The privacy issues become a major problem that should be resolved for the existing centralized online social networks, which have prompted researchers to consider the decentralization framework for online social networks. In this paper, we propose a novel decentralized social networking architecture enhanced by blockchain technology. We use a sharding framework to increase the system scalability, a blockchain system to ensure the data integrity and consistency, a reputation-based authority control method to improve the system security. © 2019 IEEE.

关键词： Blockchain

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Singular Perturbation Approach based Boundary control of a Flexible Manipulator with High Gain Observer

Singular Perturbation Approach based Boundary Control of a F...

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第三十八届中国控制会议

作者： Zhijie Liu Hongjun Yang Yan Yang School of Automation and Electrical Engineering University of Science and Technology Beijing The State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences School of Electro-Mechanical Engineering Xidian University

In this study, boundary control of a flexible manipulator is developed on the basis of the dynamic, partial differential equation(PDE) model. One of the main contributions is that the high gain observer is first applied to the PDE model of a flexible manipulator instead of measuring link velocity and end actuator velocity. In addition, using singular perturbation approach the PDE model is divided into two simpler subsystems to simplify the control design. Based on the proposed observer and decoupled PDE model, a sliding mode boundary control is designed to regulate angular position and suppress elastic vibration simultaneously. Numerical simulations demonstrate the effectiveness of the proposed scheme.

关键词： Boundary control flexible manipulator PDE model high gain observer singular perturbation

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