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International Joint Conference on Neural Networks

作者： Bo Zhao Derong Liu Yuanchun Li Guang Shi State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Automation and Electrical Engineering University of Science and Technology Beijing Department of Control Science and Engineering Changchun University of Technology

ISBN: (纸本)9781509006212

This paper develops a novel fault compensation control scheme based on adaptive dynamic programming for nonlinear systems with actuator failures. The control scheme consists of a policy iteration algorithm and a fault compensation. For fault-free dynamic models, the Hamilton-Jacobi-Bellman equation is solved by policy iteration algorithm via constructing a critic neural network, and then the approximate optimal control policy can be derived directly. On the other hand, the online fault compensation is achieved without the fault detection and isolation mechanism by reconstructing the actuator failure. The closed-loop system is guaranteed to be asymptotically stable based on Lyapunov stability theorem. Two simulation examples are given to demonstrate the effectiveness of the present fault compensation control scheme.

关键词： Iterative algorithms Nonlinear systems compensator control dynamic programming Defect detection faults actuators system failures

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Towards Blockchain-based Intelligent Transportation systems

Towards Blockchain-based Intelligent Transportation Systems

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IEEE International Conference on Intelligent Transportation systems

作者： Yong Yuan Fei-Yue Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences (SKL-MCCS CASIA) Beijing 100190 China SKL-MCCS CASIA China

ISBN: (纸本)9781509018901

Blockchain, widely known as one of the disruptive technologies emerged in recent years, is experiencing rapid development and has the full potential of revolutionizing the increasingly centralized intelligent transportation systems (ITS) in applications. Blockchain can be utilized to establish a secured, trusted and decentralized autonomous ITS ecosystem, creating better usage of the legacy ITS infrastructure and resources, especially effective for crowdsourcing technology. This paper conducts a preliminary study of Blockchain-based ITS (B~2ITS). We outline an ITS-oriented, seven-layer conceptual model for blockchain, and on this basis address the key research issues in B~2ITS. We consider that blockchain is one of the secured and trusted architectures for building the newly developed parallel transportation management systems (PtMS), and thereby discuss the relationship between B~2ITS and PtMS. Finally, we present a case study for blockchain-based realtime ride-sharing services. In our viewpoint, B~2ITS represents the future trend of ITS research and practice, and this paper is aimed at stimulating further effort and providing helpful guidance and reference for future research works.

关键词： Peer-to-peer computing Ecosystems Cryptography Vehicles complexity theory

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Scene-specific pedestrian detection based on parallel vision

arXiv

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arXiv 2017年

作者： Zhang, Wenwen Wang, Kunfeng Qu, Hua Zhao, Jihong Wang, Fei-Yue School of Software Engineering Xi’an Jiaotong University Xi’an710049 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Qingdao Academy of Intelligent Industries Qingdao266000 China School of Software Engineering Xi’an Jiaotong University Xi’an710049 China Department of Communication and Information Engineering Xi’an Jiaotong University Xi’an710049 China Research Center for Computational Experiments and Parallel Systems Technology National University of Defense Technology Changsha410073 China

As a special type of object detection, pedestrian detection in generic scenes has made a significant progress trained with large amounts of labeled training data manually. While the models trained with generic dataset work bad when they are directly used in specific scenes. With special viewpoints, flow light and backgrounds, datasets from specific scenes are much different from the datasets from generic scenes. In order to make the generic scene pedestrian detectors work well in specific scenes, the labeled data from specific scenes are needed to adapt the models to the specific scenes. While labeling the data manually spends much time and money, especially for specific scenes, each time with a new specific scene, large amounts of images must be labeled. What’s more, the labeling information is not so accurate in the pixels manually and different people make different labeling information. In this paper, we propose an ACP-based method, with augmented reality’s help, we build the virtual world of specific scenes, and make people walking in the virtual scenes where it is possible for them to appear to solve this problem of lacking labeled data and the results show that data from virtual world is helpful to adapt generic pedestrian detectors to specific scenes. Copyright © 2017, The Authors. All rights reserved.

关键词： Virtual reality

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Neural-network-based robust optimal control of uncertain nonlinear systems using model-free policy iteration algorithm

Neural-network-based robust optimal control of uncertain non...

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International Joint Conference on Neural Networks

作者： Chao Li Ding Wang Derong Liu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Automation and Electrical Engineering University of Science and Technology Beijing 100083 China

ISBN: (纸本)9781509006212

In this paper, we establish a robust optimal control law for a class of continuous-time uncertain nonlinear systems by using a neural-network-based model-free policy iteration approach. The robust control law of the original uncertain nonlinear system is derived by adding a feedback gain to the optimal control law of the nominal system. It is proven that this robust control law can achieve optimality under a specified cost function. Then, the neural-network-based model-free policy iteration algorithm is developed to solve the Hamilton-Jacobi-Bellman equation corresponding to the nominal system without system dynamics. The actor-critic technique and the least squares implementation method are used to obtain the optimal control policy of the nominal system. A numerical simulation is given to verify the applicability of the present robust optimal control scheme.

关键词： Optimal control Cost function Mathematical model Heuristic algorithms Robustness Robust control Nonlinear systems

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A Process Simulation-Based Quantitative HAZOP Analysis Method

A Process Simulation-Based Quantitative HAZOP Analysis Metho...

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Jianlong Chen Xiwei Liu Sifeng Jing Gang Xiong Xiuqin Shang Changjian Cheng The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Chemical Engineering and the Environment Beijing Institute of Technology Institute of Smart Education Systems Qingdao Academy of Intelligent Industries

Hazard and operability(HAZOP) methodology is an important Process Hazard Analysis(PHA) technique for ensuring safety production in chemical industry. Due to the lacks of accuracy and reliability in manual HAZOP analysis, the quantitative HAZOP analysis has gained more and more attention. In this work, a process simulation-based HAZOP analysis method and its flow chart are proposed. And the proposed method is applied to a steam generation subsystem in an ethylene pyrolysis unit on a dynamic process simulation platform. All deviation parameters of system can be calculated and described quantitatively. The case study shows the proposed method is useful for the effective risk prevention and control measures in a chemical process.

关键词： Quantitative HAZOP process simulation Process Hazard Analysis

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NFLB Dropout:Improve Generalization Ability by Dropping out the Best-A Biologically Inspired Adaptive Dropout Method For Unsupervised Learning

NFLB Dropout:Improve Generalization Ability by Dropping out ...

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International Joint Conference on Neural Networks

作者： Peijie Yin Lu Qi Xuanyang Xi Bo Zhang Hong Qiao Institute of Applied Mathematics Academy of Mathematics and Systems Science Chinese Academy of Science State Key Lab of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781509006212

Generalization ability is widely acknowledged as one of the most important criteria to evaluate the quality of unsupervised models. The objective of our research is to find a better dropout method to improve the generalization ability of convolutional deep belief network (CDBN), an unsupervised learning model for vision tasks. In this paper, the phenomenon of low feature diversity during the training process is investigated. The attention mechanism of human visual system is more focused on rare events and depresses well-known facts. Inspired by this mechanism, No Feature Left Behind Dropout (NFLB Dropout), an adaptive dropout method is firstly proposed to automatically adjust the dropout rate feature-wisely. In the proposed method, the algorithm drops well-trained features and keeps poorly-trained ones with a high probability during training iterations. In addition, we apply two approximations of the quality of features, which are inspired by theory of saliency and optimization. Compared with the model trained by standard dropout, experiment results show that our NFLB Dropout method improves not only the accuracy but the convergence speed as well.

关键词： Training Feature extraction Brain models Adaptation models Neural networks Unsupervised learning

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Social manufacturing and business model innovation

Social manufacturing and business model innovation

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Jesse Karjalainen Xiong Gang Aalto University Department of Industrial Engineering and Management The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Science Department of Industrial Engineering and Management School of ScienceAalto University

We have witnessed the emergence of a new set of corporations that have been able to grow faster than the competition with fewer resources. Corporations such as Uber and Air Bnb have grown to become one of the largest of their kind in less than ten years: Uber was established in 2009 and is currently the world's biggest taxi company. Interestingly, it does not own any vehicles. Similarly, Air Bnb was established in 2008 and is currently is the world's largest accommodation provider. Again, interestingly, it does not own any real estate. What is happening here, and more importantly, what kind of business model innovation has taken place, if any? This paper aims to shed light on these questions by analyzing the business models of these companies and contrasting them with those of their respective industry incumbents. The results highlight the importance of software in automatizing and outsourcing otherwise capital and labor intensive activities as well as enabling the business model to build upon logical resources composed of decentralized, transient slack resources of individuals and companies.

关键词： Social manufacturing and business model innovation

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Prediction of Energy Consumption in Office Buildings Based on Echo state Network

Prediction of Energy Consumption in Office Buildings Based o...

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World Congress on Intelligent control and automation

作者： Guang Shi Derong Liu Qinglai Wei The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China

ISBN: (纸本)9781467384155

Energy consumption of an office building is generally divided into energy consumptions from sockets, lights and air-conditioners, which are measured in each room of the office building by three ammeters installed inside, respectively. On the other hand, an office building generally consists of several types of rooms, i.e., office rooms, computer rooms, storage rooms, meeting rooms, etc., the energy consumption of which varies in accordance with different working routines in each type of room. In this paper, several novel reservoir topologies of echo state network (ESN) are proposed, and ESNs with different reservoir topologies are applied to predicting energy consumption of rooms in an office building. A case study shows that the proposed simplified reservoir topologies are sufficient to achieve outstanding performance of ESN in the prediction of building energy consumption.

关键词： Energy consumption Reservoirs Buildings Topology Training Computers Sockets energy consumption office buildings Power outlets Socket Buildings reservoirs Computers topology Functional training Rooms built structure office Electronic Serial Number Air conditioners

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Adaptive Dynamic Programming for Residential Energy Scheduling with Solar Energy

Adaptive Dynamic Programming for Residential Energy Scheduli...

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World Congress on Intelligent control and automation

作者： Yancai Xu Derong Liu Qinglai Wei Biao Luo The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China

ISBN: (纸本)9781467384155

Residential energy scheduling on demand side is a hot research area for saving energy and balancing loads. In this paper, an adaptive dynamic programming method is proposed for residential energy scheduling to reduce cost between two adjacent housing units. Two sets of storage batteries and solar stations make energy scheduling problems quite complicated while using traditional methods. The scheduling algorithm is designed based on action dependent heuristic dynamic programming. In the utility function, the weighting function is given to adjust the remaining capacities of batteries. Furthermore, the temperature becomes an input of neural networks to stay close to reality. Simulation results show the effectiveness of saving cost and balancing loads.

关键词： Batteries Dynamic programming Solar energy Discharges (electric) Training Dynamic scheduling

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A Simple and Effective Method For the Use of Chemical Accident Cases

A Simple and Effective Method For the Use of Chemical Accide...

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Sifeng.Jing Xiwei.Liu Chuanzhong.Xu Institute of Smart Education Systems Qingdao Academy of Intelligent Industries The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Refinery No.2 Petro China Fushun Petrochemical Company

past chemical industry accident cases include volume valuable information like precursor, equipment involved, relevant causes and experiences of emergence response. In-depth analysis and fully utilization of these information play an important decision-making role in controlling risk and enhancing safety performance in chemical industry. In this work, a survey of use of accident data is conducted around the world and the result shows that the detailed use of these information play an important role in preventing accidents. However, in china there much more needs to be done in the application of accident data. According to the needs of safety management of chemical plants, a simple and effective method of the use of chemical accident cases is proposed based on collecting and analyzing of a large number of chemical accident cases. And finally, a utilization system of chemical industry accident cases is implemented through Microsoft access 2010. The result shows that the system can realize the effective management and use of past chemical accident information.

关键词： chemical accident cases use of information database fuzzy query chemical safety performance

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