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2018 IEEE intelligent Vehicles Symposium, IV 2018

作者： Wang, Shuai Yuan, Yong Wang, Xiao Li, Juanjuan Qin, Rui Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Qingdao Academy of Intelligent Industries Qingdao266109 China Research Center of Military Computational Experiments and Parallel Systems National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781538644522

With the rapid development of cryptocurrency and its underlying blockchain technologies, platforms such as Ethereum and Hyperledger began to support various types of smart contracts. Smart contracts are computer protocols intended to digitally facilitate, verify, or enforce the negotiation or performance of a contract. Smart contracts have broad range of applications, such as financial services, prediction markets and Internet of Things (IoT), etc. However, there are still many challenges such as security issues and privacy disclosure that await future research. In this paper, we present a comprehensive overview on blockchain powered smart contracts. First, we give a systematic introduction for smart contracts, including the basic framework, operating mechanisms, platforms and programming languages. Second, application scenarios and existing challenges are discussed. Finally, we describe the recent advances of smart contract and present its future development trends, e.g., parallel blockchain. This paper is aimed at providing helpful guidance and reference for future research efforts. © 2018 IEEE.

关键词： Smart contract

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Design of an Optimization and control system for Carbon Efficiency in the Green Manufacturing of Sinter Ore 36

Design of an Optimization and Control System for Carbon Effi...

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第36届中国控制会议

作者： Sheng Du Min Wu Xin Chen Weihua Cao Jinhua She School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology

ISBN: (纸本)9781538629185

Sinter ore is the raw material of the iron and steel production.A sintering production process is with high energy consumption and large CO *** is important to achieve the green manufacturing of the sinter *** this paper,an optimization and control system for the carbon efficiency(OCSCE) in the green manufacturing of the sinter ore is designed from the point of view of the maximum utilization of the carbon and the best protection of environment in the sintering *** OCSCE has three parts:the optimization for the carbon efficiency,the coordinated optimization and control for the production phases and the comprehensive performance evaluation for the carbon *** optimization for the carbon efficiency is used to optimize the state *** coordinated optimization and control for the production phases is applied to optimize and control the operation *** comprehensive performance evaluation for the carbon efficiency assesses whether the carbon efficiency of the whole sintering process is consistent with green ***,an implementation scheme of the OCSCE is put forward for the industrial *** results of preliminary tests show that the OCSCE is in line with the needs of the industrial site,and it will have a significant performance after the OCSCE is put into the industrial site.

关键词： Carbon Efficiency Sintering Process Optimization Evaluation Hierarchical Structure

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Effective approach for outdoor obstacle detection by clustering LIDAR data context

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Journal of Beijing Institute of Technology 2016年第4期25卷 483-490页

作者：王军政乔佳楠李静 Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology

A method of environment mapping using laser-based light detection and ranging （LIDAR） is proposed in this paper. This method not only has a good detection performance in a wide range of detection angles, but also facilitates the detection of dynamic and hollowed-out obstacles. Essentially using this method, an improved clustering algorithm based on fast search and discovery of density peaks （CBFD） is presented to extract various obstacles in the environment map. By comparing with other cluster algorithms, CBFD can obtain a favorable number of clusterings automatically. Furthermore, the experiments show that CBFD is better and more robust in functionality and performance than the K-means and iterative self-organizing data analysis techniques algorithm （ISODATA）.

关键词： context modeling clustering algorithm based on fast search and discovery of densitypeaks（CBFD） Hull algorithm obstacle detection obstacle fusion

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Multi objective optimization based on SPEA for the microgrid energy dispatch

Multi objective optimization based on SPEA for the microgrid...

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第37届中国控制会议

作者： Xiaomin Wu Weihua Cao Dianhong Wang Min Ding School of Automation China University of Geosciences Hubei KEY Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Mechanical Engineering and Electronic Information China University of Geosciences

Microgrid provides an effective technical approach for distributed generation system connected to the power *** are renewable sources such as wind power, photovoltaic in the microgrid, which the power volatility of distributed generation limits the effective scheduling and real-time performance of microgrid. Energy storage device is used to stabilize the volatility of distributed generation, make sure the feasibility of distributed generation optimal scheduling. Microgrid optimizes scheduling the energy allocation od various types of distributed generation in technology, economy, environment and other aspects. In order to solutio the multi objective optimization of microgrid energy allocation, a Strength Pareto Evolutionary Algorithm based optimal method was proposed. Finally, the correctness and feasibility of the proposed method were verified through the simulation.

关键词： Microgrid Distributed generation Multi objective optimization Strength Pareto Evolutionary Algorithm

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A Dynamic Data-driven Model for Predicting Strip Temperature in Continuous Annealing Line Heating Process

A Dynamic Data-driven Model for Predicting Strip Temperature...

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Chinese control Conference (CCC)

作者： Yongyue Zhang Yali Jin Weihua Cao Zezhong Li Yan Yuan School of Information Science and Engineering Central South University Changsha Hunan China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei China

In the continuous annealing line heating process, it is hard to get an accurate predict result only by a steady state model as it is a complex, strongly time-delayed and confounding process. This study provides a method for building a dynamic model. First analyzes the mechanism of the annealing line to get the main parameters, and then use the data-driven modeling method to get a steady state model, finally combines with dynamic algorithm to establish a dynamic model. This modeling method improves the accuracy of predict result to guarantee the efficiency of enterprises.

关键词： Heating systems Strips Mathematical model Predictive models Furnaces Process control Data models

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Economic Issues in Bitcoin Mining and Blockchain Research

Economic Issues in Bitcoin Mining and Blockchain Research

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2018 IEEE intelligent Vehicles Symposium, IV 2018

作者： Qin, Rui Yuan, Yong Wang, Shuai 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 Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Research Center of Military Computational Experiments and Parallel Systems National University of Defense Technology Changsha China

ISBN: (纸本)9781538644522

With the development of the blockchain technology, Bitcoin mining has become more and more popular. This paper aims to provide a three-level framework of the economic issues in Bitcoin mining research, from the levels of mining pools, individual miners and blockchain network. We also offer an overview of relevant research efforts in literature. Considering the uncertainty, diversity and complexity of the Bitcoin ecosystems, we propose a novel research framework based on the ACP theory, which can be used to explore the economic issues in the Bitcoin ecosystems. This paper aims to provide a preliminary investigation to the economic issues faced by participants in the Bitcoin ecosystems, and stimulate the attentions and interests of researchers in this field. © 2018 IEEE.

关键词： Blockchain

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ADP-Based Model Reference Adaptive control Design for Unknown Discrete-Time Nonlinear systems

ADP-Based Model Reference Adaptive Control Design for Unknow...

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第37届中国控制会议

作者： Wei Wang Xin Chen Fang Wang Hao Fu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Electrical and Information Engineering Zhengzhou University of Light Industry

In engineering applications, it is very useful to make a nonlinear system behave like a linear stable system. However,how to design a model reference adaptive control（MRAC） as the nonlinear dynamics is unknown is the key problem. In this study,an MRAC with adaptive dynamic programming（ADP） algorithm is presented for discrete-time nonlinear unknown dynamic systems, in which a multi-layer neural network（NN） model is utilized to describe the nonlinear system’s dynamics. Then based on this approximate model, a feedforward neuro-controller is developed as the desired control corresponding to the reference input. Third, the iterative ADP algorithm, in the form of actor-critic framework, employs two NNs to estimate the action value function, and generates the feedback control which, together with the feedforward neuro-controller, makes the state of the system track the reference model. Finally the feasibility of the new approach is verified by two numerical experiments.

关键词： Model reference adaptive control Adaptive dynamic programming Nonlinear system Q-function

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State Estimation and Fault Detection for Nonlinear Dynamic systems

State Estimation and Fault Detection for Nonlinear Dynamic S...

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Chinese control Conference (CCC)

作者： Baohua Lu Liping Yan Hongxue Chen Yuanqing Xia Mengyin Fu Bo Xiao Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

In practical problems, the dynamic systems are usually nonlinear. In this case, the traditional Kalman filter cannot be used for state estimation or fault detection. The two typical extension based on Kalman filtering framework is the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF). Theoretically speaking, UKF is better than EKF when estimation accuracy is concerned, especially for high degree nonlinear cases. This paper is concerned with the state estimation and fault detection problem for a class of nonlinear dynamic systems. A novel fault detection and analyse method is presented based on the period residual of EKF and UKF. For different kind of faults, mainly, the system parameter error, the sensor/data error, EKF and UKF are used and the estimation and fault detection effects are compared and analyzed.

关键词： Fault detection Mathematical model State estimation Kalman filters Nonlinear systems Jacobian matrices

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A general decoupled AC/DC power flow algorithm with VSC-MTDC

A general decoupled AC/DC power flow algorithm with VSC-MTDC

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Shilin Gao Hua Ye Yanling Du Haitao Liu Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China State Grid Jibei Electric Power Company Beijing China

For a large scale hybrid AC/DC system, it is of great significance to find a power flow algorithm with good convergence and short calculation time. For the purpose, this paper presents a decoupled power flow algorithm for hybrid AC/DC system containing voltage source converter based multiterminal high voltage direct current (VSC-MTDC) grids. By redefining the boundary of the AC and DC grids at DC side of the VSCs, the power flow calculation (PFC) of the AC grid and the DC grid is decoupled. The VSC station is regarded as one part of the AC grid. Therefore, the power flow of the station is calculated in the AC grid PFC. Additionally, certain adjustments and simplifications are employed to the mismatch equations and Jacobian matrix of DC grids, which is time-saving. For generality, the loss model of the converter and various control strategies of the VSC station are detailedly considered. PFC of a modified New England 10-machine 39-bus test system is executed to show the validity and efficiency of the proposed algorithm.

关键词： Load flow Mathematical model Power conversion Jacobian matrices Voltage control Hybrid power systems

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A Variational Bayesian Labeled Multi-Bernoulli Filter for Tracking with Inverse Wishart Distribution

A Variational Bayesian Labeled Multi-Bernoulli Filter for Tr...

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International Conference on Information Fusion

作者： Jinran Wang Zhongliang Jing Peng Dong Jin Cheng School of Aeronautics and Astronautics Shanghai Jiao Tong University Shanghai China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-mechanical Engineering Institute Beijing China

In multi-target tracking (MTT), the imprecise model for sensor characteristics might result in poor performance. The Variational Bayesian labeled multi-Bernoulli (VB-LMB) filter based on Gamma distribution can handle this problem. However, the predictive likelihood of the existing VB-LMB filter is simply treated as a Gaussian, which is inaccurate. In this paper, a VB-LMB filter with inverse Wishart distribution is presented to perform MTT under the unknown sensor characteristics. The measurement noise covariance is modeled as an inverse Wishart (IW) distribution. This distribution has potential to deal with the full noise covariance matrix compared with the Gamma distribution. Since the state and the measurement noise covariance are coupled, the updated equation can be solved by variational Bayesian (VB) method. The predictive likelihood is calculated via minimizing the Kullback-Leibler divergence by the VB lower bound. A MTT scenario is used to evaluate the proposed method. Simulation results show that our approach has better performance than the existing VB-LMB filter with the Gamma distribution.

关键词： Radio frequency Noise measurement Bayes methods Covariance matrices Target tracking Extraterrestrial measurements

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