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

作者： Xinzhu Wang Xiaoyan Gong Xiwei Liu Yan Yan Nan Zhang Jie Luo Faculty of Education Beijing Normal University Beijing China Institute of Smart Education Qingdao Academy of Intelligent Industries Qingdao China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Chinese Association of Automation Beijing China The State Key Laboratory of Software Development Environment Beihang University Beijing China

Teacher's Online Practice in Community (TOPIC) is an informal and practical online learning community that improves teachers' professional development. Domestic researches on TOPIC have begun to take shape. By sorting out relevant literature retrieved from China National Knowledge Infrastructure (CNKI), this article summarizes research topics such as knowledge management, teacher professional development, and community management and summarizes qualitative and quantitative research methods commonly used by domestic researches. This article finally puts forward some limitations of current researches in this field and forecasts the possible future research directions.

关键词： Knowledge transfer Training Reflection Organizations Focusing

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A Multi-model Estimation of Distribution Algorithm for Agent Routing Problem in Multi-point Dynamic Task

A Multi-model Estimation of Distribution Algorithm for Agent...

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第37届中国控制会议

作者： Sai Lu Bin Xin Lihua Dou Ling Wang School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Advanced Innovation Center for Intelligent Robots and Systems Department of Automation Tsinghua University

The agent routing problem in multi-point dynamic task（ARP-MPDT） is a multi-task routing problem of a mobile agent. In this problem, there are multiple tasks to be carried out in different locations. As time goes on, the state of each task will change nonlinearly. The agent must go to the task points in turn to perform the tasks, and the execution time of each task is related to the state of the task point when the agent arrives at the point. ARP-MPDT is a typical NP-hard optimization problem. In this paper, we establish the nonlinear ARP-MPDT model. A multi-model estimation of distribution algorithm（EDA） employing node histogram models（NHM） and edge histogram models（EHM） in probability modeling is used to solve the ARP-MPDT. The selection ratio of NHM and EHM probability models is adjusted adaptively. Finally, performance of the algorithm for solving the ARP-MPDT problem is verified by the computational experiments.

关键词： Estimation of distribution algorithm Multi-model Routing Multi-point dynamic task

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ICB-MOEA/D: An interactive classification-based multi-objective optimization algorithm

ICB-MOEA/D: An interactive classification-based multi-object...

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第37届中国控制会议

作者： Bin Xin Hepeng Li Ling Wang School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Advanced Innovation Center for Intelligent Robots and Systems Department of Automation Tsinghua University

Interactive multi-objective optimization algorithms have developed rapidly in recent years. In this paper, we propose a new classification-based interactive multi-objective optimization algorithm named ICB-MOEA/D to solve the formulated multiobjective optimization problem. ICB-MOEA/D provides several solutions for the decision maker to choose. The decision maker chooses his/her most preferred solution from these solutions and the historical solutions which have been chosen as the current most preferred solution. ICB-MOEA/D records this solution and classifies the objectives according to the updated preference information into four categories: 1) objectives which are expected to be improved;2) objectives which can be sacrificed;3) objectives which are expected to remain basically unchanged;4) objectives which do not matter currently. Accoding to the number of the objectives in the first category, a new single-objective opitimization model or multi-objective optimization model will be built. The single-objective optimization model will be optimized by a classic variant of differential evolution DE/rand/1/bin, and the multi-objective optimization model will be optimized by a popular docomposition-based multi-objective optimizer MOEA/*** the classifications are done automatically by the algorithm, reducing the burden of the decision maker. ICB-MOEA/D was tested on the two-objective instance ZDT1, and the experiment results show the effectiveness of ICB-MOEA/D.

关键词： interactive multi-objective optimization decomposition classification virtual decision maker

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Stochastic optimal control for sampled-data system under stochastic sampling

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IET control Theory & Applications 2018年第11期12卷 1553-1560页

作者： Haoyuan Sun Jie Chen Jian Sun School of Automation Beijing Institute of Technology Beijing 100081 People's Republic of China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081 People's Republic of China

In this study, the problem of designing a stochastic optimal controller for sampled-data systems whose sampling interval is subjected to a certain probability distribution is addressed. To design the controller, the Kronecker product operation and the Vandermonde matrix were introduced. A design method of the stochastic optimal controller is proposed. It is shown that the controller guarantee that the closed-loop system has exponentially mean square stability. Finally, the simulation results illustrate the effectiveness and practicability of the proposed method.

关键词： sampled data systems control system synthesis stochastic systems stochastic processes closed loop systems optimal control asymptotic stability sampling methods statistical distributions matrix algebra stochastic optimal control sampled-data system stochastic sampling sampling interval stochastic optimal controller design probability distribution Kronecker product operation Vandermonde matrix closed-loop system exponentially mean square stability

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A Vision and Neural Network Based Air-Ground Coordinated control System

A Vision and Neural Network Based Air-Ground Coordinated Con...

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2017 IEEE International Conference on Unmanned systems (ICUS)

作者： Muyun Jiang Jiahui Shi Hongbin Ma You Li School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781538631089;9781538631072

This paper presents an air-ground coordinated system made up of an Unmanned Aerial Vehicle(UAV) and an Unmanned Ground Vehicle(UGV).The movement of UGV is totally controlled by UAV and multiple sensors are adopted in the system to ensure the stability.A novel neutral network algorithm is introduced to identify the location and orientation of *** component is introduced and tested in detail and the coordinated system performs a satisfying result.

关键词： Air-ground system Neutral Network

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Trajectory tracking of under-actuated reentry vehicle based on time-varying SMC with RBF disturbance observer 5

Trajectory tracking of under-actuated reentry vehicle based ...

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5th International Workshop on Advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Ji, Haibo Guo, Fuhui Liu, Xiangdong School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

In this paper, an effective guidance scheme and a control scheme are proposed to realize trajectory tracking of hypersonic reentry vehicle(HRV) subject to aileron stuck in some position. The overload is adopted as virtual control instead of lift and lateral force, then guidance order can be obtained by torque coefficient function. In attitude subsystem, attack of angle and sideslip angle are controlled to track guidance order. Time-varying sliding mode control method is adopted to design guidance law and attitude controller. Besides, a RBF observer is designed to estimate the unknown external disturbance to soften the chattering caused by TVSMC. Simulations verify the proposed schemes.

关键词： Sliding mode control

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Optimal Rescue Path for Maritime Air Crash Based on Probability Density Distribution and Bayesian Formula

Optimal Rescue Path for Maritime Air Crash Based on Probabil...

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第37届中国控制会议

作者： Jing Wang Ping Yu Zhen-Tao Liu State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang University Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Optimal rescue path for maritime air crash based on probability density distribution and Bayesian formula is proposed,where probable crash area is determined through surface search at a high altitude,and then the minimum wreckage floating zone is obtained by probability density ***,we divide it into regular hexagons based on Honeycomb Model to identify the point search area that is endowed with priority by Bayesian ***,the optimal path is worked out by transferring optimization problem to be a Traveling Salesman Problem(TSP).In simulations,some spots are randomly chosen on a Google map in which we can find debris in ocean through surface search at high *** a point search route is obtained by using Annealing algorithm,which strips out 4%of time compared with current *** intelligent search and rescue framework based on reinforcement learning is *** future work,search and rescue work will be free from manpower and bad weather constraints.

关键词： Point search Hexagonal regions Priority Bayesian formula Traveling Salesman Problem Reinforcement Learning

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A maximum power point tracking controller for thermoelectric generators 36

A maximum power point tracking controller for thermoelectric...

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第36届中国控制会议

作者： Wei Xie Guangyue Huang Xiao Zhang Fang Deng School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems China ZhenHua Oil Co

ISBN: (纸本)9781538629185

Thermoelectric generators（TEGs） directly convert heat energy into electricity for power-supplying sensors and other portable electronic *** this paper,a maximum power point tracking（MPPT） controller in the modified perturb and observe（P＆O） algorithm was designed on the basis of analyzing the output characteristics of the TEG *** MPPT controller consists of a voltage sensor,a current sensor,a microcontroller and a SEPIC converter,which keeps the operating point of the thermoelectric generator tracking the maximum power point（MPP）.The thermoelectric generator was heated to generate electricity,and a supercapacitor accumulated that *** results using the MPPT controller present that the thermoelectric generator’s output voltage achieves around 5V,the output power achieves upward of 2W when the temperature difference △T=75℃,and the operating point of the thermoelectric generator accurately tracks the MPP with a tracking efficiency of 99.8%;the charging power can be improved 89.65%.

关键词： Thermoelectric generators（TEGs） Modified P＆O algorithm Maximum power point tracking（MPPT） SEPIC converter

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Distributed Algorithm for Discrete-Time Lyapunov Equations

Distributed Algorithm for Discrete-Time Lyapunov Equations

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International Conference on control, Automation, Robotics and Vision

作者： Xia Jiang Xianlin Zeng Jian Sun Jie Chen Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China Ministry of Education Beijing Institute of Technology Beijing China

This paper investigates the problem of solving a unique solution to discrete-time Lyapunov equations (DTLE) using multi-agent networks. We propose a distributed algorithm where each agent only uses partial information of the matrices. The agents of the algorithm reach a consensus by exchanging information with their neighbors over an undirected connected graph. We provide convergence analysis and the convergence rate estimate for the proposed algorithm. Finally, convergence performance is verified by numerical simulations.

关键词： Distributed algorithms Mathematical model Convergence Optimization Radio frequency Convex functions Symmetric matrices

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Stability of linear systems with sawtooth input delay and predictor-based controller

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Automatica 2020年 117卷

作者： Haoyuan Sun Jian Sun Jie Chen School of Automation Beijing Institute of Technology Beijing 100081 PR China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing 100081 PR China School of Electronic and Information Engineering Tongji University Shanghai 200082 PR China

In this paper, the stability of linear systems with sawtooth input delay widely existing in networked systems and predictor-based controller is considered. Under the assumption that there exists an instant where the input delay is zero, a necessary and sufficient condition is obtained to guarantee the exponential stability of the closed-loop system, that is, the closed-loop system is stable if and only if the matrix A + B K is Hurwitz. Two simulation examples are given to confirm the validity of the obtained results.

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