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第35届中国控制会议

作者： Chongling Li Tao Cai Zeyu Han School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

ISBN: (纸本)9781509009107

Disturbance widely exists in control *** disturbance rejection control(ADRC) has been proved to be an efficient way to deal with disturbance and achieves great success in *** most important part of ADRC is extended state observer(ESO),which estimates the states of system and total *** regards internal disturbance and external disturbance as a total disturbance,estimates it and eliminates it in the *** faster ESO estimates total disturbance,the more quickly controller eliminates *** paper focuses on the discrete linear extended state observer(DLESO),and presents discrete predictive linear extended state observer(DPLESO).Stability and performances are *** result shows that DPLESO has better performances for disturbance rejection than DLESO.

关键词： disturbance discrete ADRC LESO predictive linear extended state observer

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How to “STEAM” Children at Home? Let Children “STEAM” Themselves

How to “STEAM” Children at Home? Let Children “STEAM” Th...

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Xiaoyan Gong The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Institute of Smart Education Systems Qingdao Academy of Intelligent Industries

In this article, I would like to share my daughter's experience on self-STEAM education. In our daily life, she can always find problems and then dream them with her imagination, finally narrows down her solutions to solve problems in her own way. During these problem-solving processes, I noticed that she went through sciences, technology, engineering, arts and mathematics in a very natural way. So I would like to say, STEAM is the way we learn and grow ever since we were born. But later at school, we are trained in a way that subjects are completely disconnected. It might take time to change this situation at school, but at home, as parents, we need to realize that children can discover new things by themselves even from young ages, and provide rich learning environment for them and let them "STEAM " themselves in their own way.

关键词： STEM STEAM education maker education

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An Improved Part-based Compressive Tracking Method

An Improved Part-based Compressive Tracking Method

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第35届中国控制会议

作者： Qiwen Hou Wenjie Chen HuiLin Gao School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

ISBN: (纸本)9781509009107

In this paper,we propose an improved part-based tracking method based on compressive *** traditional compressive tracking can hardly deal with occlusion and scale variation,which is not robust enough in these *** our part-based method,the occluded image patches which are selected by K-means are not able to participate in determining the location of the target in order to increase tracking *** solve the problem of scale variation,an algorithm is proposed to estimate the size of target with the information of the whole *** addition,we also use the positions of every part to help us to get a precise size of the *** the combination of two methods,the scale of the target is *** compared with five state-of-the-arts have been done to prove the effectiveness and robustness of our method.

关键词： compressive sensing part-based tracking occlusion handling scale estimation

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A General Adaptive Dynamic Programming Approach with Experience Replay

A General Adaptive Dynamic Programming Approach with Experie...

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International Joint Conference on Neural Networks

作者： Bin Wang Dongbin Zhao Jin Cheng Yuan Xu Yueyang Li School of Electrical Engineering University of Jinan The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781509006212

Experience replay is a promising approach to improve the learning efficiency of adaptive dynamic programming. A general model-free adaptive dynamic programming (ADP) approach with the experience replay technology is investigated in this paper to solve the optimal control problems in continuous state and action spaces. Both the critic network and action network are modeled with a feedforward neural network with one hidden layer. During the learning process, a number of recently observed data samples are recorded in a database. When updating the parameters of the neural networks, the data in the sample database are repeatedly used to update the weights of the action network and the critic network. Implementation details of the algorithm are given, and simulation experiments are utilized to verify the learning efficiency of the proposed approach.

关键词： Erbium Dynamic programming Neural networks Databases Optimal control Heuristic algorithms Approximation algorithms

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Optimal Self-Learning control Scheme for Discrete-Time Nonlinear systems Using Local Value Iteration

Optimal Self-Learning Control Scheme for Discrete-Time Nonli...

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International Joint Conference on Neural Networks

作者： 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 optimal self-learning control scheme for discrete-time nonlinear systems is developed using a new local value iteration based adaptive dynamic programming (ADP) algorithm. The developed local value iteration algorithm permits an arbitrary positive semi-definite function to initialize the algorithm. In the developed local value iteration algorithm, the iterative value function and iterative control law are updated by a subset of the state space. A new analysis method of the convergence property is presented to show that the iterative value functions will converge to the optimum. The convergence criterion for the local value iteration algorithm is presented. A simulation example is given to demonstrate the validity of the present optimal control scheme.

关键词： state-space methods convergence discrete time systems dynamic programming iterative methods learning systems nonlinear systems optimal control

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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...

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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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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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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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Convolutional Fitted Q Iteration For Vision-Based control Problems

Convolutional Fitted Q Iteration For Vision-Based Control Pr...

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International Joint Conference on Neural Networks

作者： Dongbin Zhao Yuanheng Zhu Le Lv Yaran Chen Qichao Zhang State Key Laboratory of Management and Control for Complex Systems Institution of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781509006212

In this paper a deep reinforcement learning (DRL) method is proposed to solve the control problem which takes raw image pixels as input states. A convolutional neural network (CNN) is used to approximate Q functions, termed as Q-CNN. A pretrained network, which is the result of a classification challenge on a vast set of natural images, initializes the parameters of Q-CNN. Such initialization assigns Q-CNN with the features of image representation, so it is more concentrated on the control tasks. The weights are tuned under the scheme of fitted Q iteration (FQI), which is an offline reinforcement learning method with the stable convergence property. To demonstrate the performance, a modified Food-Poison problem is simulated. The agent determines its movements based on its forward view. In the end the algorithm successfully learns a satisfied policy which has better performance than the results of previous researches.

关键词： Feature extraction Artificial neural networks Learning (artificial intelligence) Biological neural networks Image representation Convergence Aerospace electronics

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Steps toward Parallel Intelligence

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IEEE/CAA Journal of Automatica Sinica 2016年第4期3卷 345-348页

作者： Fei-Yue Wang Xiao Wang Lingxi Li Li Li IEEE State Key Laboratory of Management and Control for Complex Systems (SKL-MCCS) Institute of AutomationChinese Academy of Sciences (CASIA) Research Center of Computational Experiments and Parallel Systems the National University of Defense Technology Qingdao Academy of Intelligent Industries (QAII) QingdaoShandongChinaand SKL-MCCSCASIA Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University Indianapolis Department of Automation Tsinghua University Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies

The origin of artificial intelligence is investigated, based on which the concepts of hybrid intelligence and parallel intelligence are presented. The paradigm shift in Intelligence indicates the ''new normal'' of cyber-social-physical systems (CPSS), in which the system behaviors are guided by Merton's Laws. Thus, the ACP-based parallel intelligence consisting of Artificial societies, Computational experiments and Parallel execution are introduced to bridge the big modeling gap in CPSS. © 2014 Chinese Association of automation.

关键词： control systems Electrical engineering

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