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检索条件"机构=State Key Laboratory of Intelligent Control and Management of Complex Systems"

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Generalized Policy Iteration Adaptive Dynamic Programming Algorithm for Optimal Tracking control of a Class of Nonlinear systems

Generalized Policy Iteration Adaptive Dynamic Programming Al...

引用

第28届中国控制与决策会议

作者： Qiao Lin Qinglai Wei Derong Liu The 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

ISBN: (纸本)9781467397155

This paper deals with optimal tracking control problems for a class of discrete-time nonlinear systems using a generalized policy iteration adaptive dynamic programming(ADP) ***,by system transformation,the optimal tracking control problem is transformed into an optimal regulation *** the generalized policy iteration ADP algorithm is employed to obtain the optimal tracking controller with convergence and optimality *** developed algorithm uses the idea of two iteration procedures to obtain the iterative tracking control laws and the iterative value *** neural networks,including model network,critic network and action network,are used to implement the developed *** last,an simulation example is given to demonstrate the effectiveness of the developed method.

关键词： adaptive dynamic programming affine nonlinear systems discrete-time generalized policy iteration neural network tracking control

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Data-Based Self-Learning Optimal control for Continuous-Time Unknown Nonlinear systems With Disturbance

Data-Based Self-Learning Optimal Control for Continuous-Time...

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第28届中国控制与决策会议

作者： Qinglai Wei Derong Liu Ruizhuo Song Pengfei Yan The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Automation and Electrical Engineering University of Science and Technology Beijing

ISBN: (纸本)9781467397155

In this paper,a new data-based self-learning control scheme is developed to solve infinite horizon optimal control problems for continuous-time nonlinear *** developed optimal control scheme can be implement without knowing the mathematical model of the *** to the input-output data of the nonlinear systems,a recurrent neural network(RNN) is employed to reconstruct the dynamics of the nonlinear *** to the RNN model of the system,a new two-person zero-sum adaptive dynamic programming(ADP) algorithm is developed to obtain the optimal control,where the reconstruction error and the system disturbance are considered the control input of the ***-layer neural networks are used to construct the critic and action networks,which are presented to approximate the performance index function and the control law,***,simulation results will show the effectiveness of the developed data-based ADP methods.

关键词： Adaptive critic designs Adaptive dynamic programming Approximate dynamic programming Neurodynamic programming Recurrent neural network Data-based control Optimal control

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An Adaptive Dynamic Programming Based Method for Optimization of Electricity Consumption in Office Buildings

An Adaptive Dynamic Programming Based Method for Optimizatio...

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International Joint Conference on Neural Networks

作者： Guang Shi Qinglai Wei Derong Liu The 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

ISBN: (纸本)9781509006212

In this paper, an adaptive dynamic programming (ADP) based method is developed to optimize electricity consumption of rooms in office buildings through optimal battery management. Rooms in office buildings are generally divided into office room, computer room, storage room, meeting room, etc., each of which has different characteristics of electricity consumption, as divided into electricity consumption from sockets, lights and air-conditioners in this paper. The developed method based on ADP is elaborated, and different optimization strategies of electricity consumption in different categories of rooms are proposed in accordance with the developed method. Finally, a detailed case study on an office building is given to show the practical effect of the developed method.

关键词： electricity consumption office buildings Rooms office Air conditioners built structure Buildings Automatic data processing Adenosine Diphosphate dynamic programming

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ADP with MCTS algorithm for Gomoku

ADP with MCTS algorithm for Gomoku

引用

IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Zhentao Tang Dongbin Zhao Kun Shao Le L.V. The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Institute of Automation Chinese Academy of Sciences Beijing Beijing CN

ISBN: (纸本)9781509042418

Inspired by the core idea of AlphaGo, we combine a neural network, which is trained by Adaptive Dynamic Programming (ADP), with Monte Carlo Tree Search (MCTS) algorithm for Gomoku. MCTS algorithm is based on Monte Carlo simulation method, which goes through lots of simulations and generates a game search tree. We rollout it and search the outcomes of the leaf nodes in the tree. As a result, we obtain the MCTS winning rate. The ADP and MCTS methods are used to estimate the winning rates respectively. We weight the two winning rates to select the action position with the maximum one. Experiment result shows that this method can effectively eliminate the neural network evaluation function's “short-sighted” defect. With our proposed method, the game's final prediction result is more accurate, and it outperforms the Gomoku with ADP algorithm.

关键词： Games Monte Carlo methods Biological neural networks Learning (artificial intelligence) Heuristic algorithms Dynamic programming

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Ensemble LSDD-based Change Detection Tests

Ensemble LSDD-based Change Detection Tests

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International Joint Conference on Neural Networks

作者： Li Bu Cesare Alippi Dongbin Zhao The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Politecnico di Milano Milano Italy and Universita Svizzera Italiana

ISBN: (纸本)9781509006212

The least squares density difference change detection test (LSDD-CDT) has proven to be an effective method in detecting concept drift by inspecting features derived from the discrepancy between two probability density functions (pdfs). The first pdf is associated with the concept drift free case, the second to the possible post change one. Interestingly, the method permits to control the ratio of false positives. This paper introduces and investigates the performance of a family of LSDD methods constructed by exploring different ensemble options applied to the basic CDT procedure. Experiments show that most of proposed methods are characterized by improved performance in change detection once compared with the direct ensemble-free counterpart.

关键词： Probability density function Concept Drift density difference carbohydrate-deficient transferrin False-positives family

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

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 Beijing China Refinery No.2 PetroChina Fushun Petrochemical Company Fushun China

ISBN: (纸本)9781509029280

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： Accidents Chemicals Databases Petrochemicals Chemical industry Safety management

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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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An answer recommendation algorithm for medical community question answering systems

An answer recommendation algorithm for medical community que...

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

作者： Jing Wang Chuntao Man Yifei Zhao Feiyue Wang College of Automation Harbin University of Science & Technology Harbin Heilongjiang Province China The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781509029280

Online medical community question answering (cQA) systems are playing important roles as a supplement of the traditional medical service systems. The answer recommendation service provides guidance to diagnose diseases and brings convenience and valuable reference to users. In this paper, we propose a method to recommend answer for particular questions on medical cQA system. There are three steps for the answer recommendation system, including similar cases retrieval, answers quality estimation and answer recommendation. The proposed algorithm is tested on a dataset collected from online medical community question answering system. The results show a good performance in answer recommendation.

关键词： Medical services Estimation Feature extraction Training Medical diagnostic imaging Knowledge discovery History

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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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Iterative Q-learning-based nonlinear optimal tracking control

Iterative Q-learning-based nonlinear optimal tracking contro...

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IEEE Symposium Series on Computational Intelligence (SSCI)

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

ISBN: (纸本)9781509042418

A new Q-learning algorithm is developed for a class of discrete-time nonlinear systems in this paper to solve the infinite horizon optimal tracking problems. Using system transformations, the optimal tracking problem is transformed to be an optimal regulation problem. Thereafter, for the regulation system, the new Q-learning algorithm is developed in order to obtain the optimal control law. Convergence of the iterative Q functions and the admissibility of the iterative control law are analyzed. In the end, two corresponding simulation examples are presented to illustrate the performance of the newly developed algorithm.

关键词： optimal control convergence discrete time systems iterative learning control nonlinear control systems

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