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第37届中国控制会议

作者： Zhao Yin Wei He Changyin Sun Guang Li Chenguang Yang School of Automation and Electrical Engineering University of Science and Technology Beijing School of Automation Southeast University Queen Mary University of London Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology

In this paper, our main goal is to solve optimal control problem by using reinforcement learning（RL） algorithm for marine surface vessel system with known dynamic. And this algorithm is an optimal control algorithm based on policy iteration（PI）, and it can obtain the suitable approximations of cost function and the optimized control policy. There are two neural networks（NNs）, where critic NN aims to estimate the cost-to-go and actor NN is utilized to design suitable input controller and minimize the tracking error. A novel tuning method is given for critic NN and actor NN. The stability and convergence are proven by Lyapunov’s direct method. Finally, the numerical simulations are conducted to demonstrate the feasibility and superiority of presented algorithm.

关键词： Reinforcement Learning Critic Neural Networks Actor Neural Networks Lyapunov Method Marine Vessel

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Neural Network Adaptive Critic control With Disturbance Rejection 29

Neural Network Adaptive Critic Control With Disturbance Reje...

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第29届中国控制与决策会议

作者： Ding Wang Chaoxu Mu Derong Liu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Computer and Control Engineering University of Chinese Academy of Sciences School of Electrical and Information Engineering Tianjin University School of Automation and Electrical Engineering University of Science and Technology Beijing

ISBN: (纸本)9781509046584

A neural-network-based adaptive critic control method is established for continuous-time input-affine uncertain nonlinear systems to achieve disturbance *** present problem can be formulated as a two-player zero-sum differential game and the adaptive critic mechanism is employed to solve the minimax optimization problem.A neural network identifier is developed to reconstruct the unknown dynamical *** optimal control law and the worst-case disturbance law are designed by introducing and training a critic neural *** effectiveness of the present self-learning control method is also illustrated by a simulation experiment.

关键词： Adaptive critic control Adaptive dynamic programming Approximate dynamic programming Disturbance rejection Learning systems Neural networks Nonlinear control

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RF chain reduction for MIMO systems: A hardware prototype

arXiv

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arXiv 2019年

作者： Gong, Tierui Shlezinger, Nir Ioushua, Shahar Stein Namer, Moshe Yang, Zhijia Eldar, Yonina C. State Key Lab of Robotics Key Lab of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel School of Electrical Engineering Tel Aviv University Tel Aviv Israel Faculty of Electrical Engineering Technion Haifa Israel

RF chain circuits play a major role in digital receiver architectures, allowing passband communication signals to be processed in baseband. When operating at high frequencies, these circuits tend to be costly. This increased cost imposes a major limitation on future multiple-input multiple-output (MIMO) communication technologies. A common approach to mitigate the increased cost is to utilize hybrid architectures, in which the received signal is combined in analog into a lower dimension, thus reducing the number of RF chains. In this work we present a hardware prototype implementing analog combining for RF chain reduction. The prototype consists of a specially designed configurable combining board as well as a dedicated experimental setup. Our hardware prototype allows to evaluate the effect of analog combining in MIMO systems using actual communication signals. The experimental study, which focuses on channel estimation accuracy in MIMO channels, demonstrates that using the proposed prototype, the achievable channel estimation performance is within a small gap in a statistical sense from that obtained using a costly receiver in which each antenna is connected to a dedicated RF chain. Furthermore, in the considered scenarios, this gap becomes negligible when the reduction rate, i.e., the ratio of the number of RF chains to the number of antennas, is above 62.5%. Copyright © 2019, The Authors. All rights reserved.

关键词： Channel estimation

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Social Energy:Mining Energy From the Society

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IEEE/CAA Journal of Automatica Sinica 2017年第3期4卷 466-482页

作者： Jun Jason Zhang David Wenzhong Gao Yingchen Zhang Xiao Wang Xiangyang Zhao Dongliang Duan Xiaoxiao Dai Jun Hao Fei-Yue Wang Department of Electrical and Computer Engineering Ritchie School of Engineering and Computer ScienceUniversity of Denver IEEE National Renewable Energy Laboratory Qingdao Academy of Intelligent Industries(QAII) QingdaoShandongChinaand SKL-MCCSCASIA School of Automation Science and Electrical Engineering Beihang University Department of Electrical and Computer Engineering College of Engineering and Applied ScienceUniversity of Wyoming State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences(SKL-MCCSCASIA) Research Center of Computational Experiments and Parallel Systems National University of Defense Technology

The inherent nature of energy,i.e.,physicality,sociality and informatization,implies the inevitable and intensive interaction between energy systems and social *** this perspective,we define "social energy" as a complex sociotechnical system of energy systems,social systems and the derived artificial virtual systems which characterize the intense intersystem and intra-system *** recent advancement in intelligent technology,including artificial intelligence and machine learning technologies,sensing and communication in Internet of Things technologies,and massive high performance computing and extreme-scale data analytics technologies,enables the possibility of substantial advancement in socio-technical system optimization,scheduling,control and *** this paper,we provide a discussion on the nature of energy,and then propose the concept and intention of social energy systems for electrical power.A general methodology of establishing and investigating social energy is proposed,which is based on the ACP approach,i.e., "artificial systems"(A), "computational experiments"(C) and "parallel execution"(P),and parallel system methodology.A case study on the University of Denver(DU) campus grid is provided and studied to demonstrate the social energy *** the concluding remarks,we discuss the technical pathway,in both social and nature sciences,to social energy,and our vision on its future.

关键词： ACP distribution locational marginal pricing intelligent operation in power systems parallel control parallel intelligence parallel management social energy socio-technical energy systems

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Simulation and Evaluation of CAVs Behavior in an Isolated Signalized Intersection Equipped with Dynamic Wireless Power Transfer System

Simulation and Evaluation of CAVs Behavior in an Isolated Si...

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International Conference on Intelligent Transportation

作者： Qingyun Liu Simon Hu Panagiotis Angeloudis Yibing Wang Lihui Zhang Qiang Yang Yongfu Li ZJU-UIUC Institute Zhejiang University Zhejiang China Department of Civil and Environmental Engineering Imperial College London London UK Institute of Intelligent Transportation Systems School of Civil Engineering and Architecture Zhejiang University Zhejiang China College of Electrical Engineering Zhejiang University Hangzhou China Key Laboratory of Intelligent Air-Ground Cooperative Control for Universities in Chongqing College of Automation Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (纸本)9781538670255

This paper proposes an idea of charging eco-driving connected autonomous vehicles (CAVs) which drive smoothly passing signalized intersection above a dynamic wireless power transfer (DWPT) system consisting of segmented coils at the upstream of approaching lanes. Mixed traffic streams with different penetration levels of eco-driving CAVs passing through a DWPT system-equipped signalized intersection are simulated using microscopic traffic simulation software PTV-VISSIM. Energy stored, which is defined as the result of energy transferred to the vehicle battery by DWPT system subtracting energy consumed by the vehicle battery whilst travelling the same distance, is used to evaluate the total impact of eco-driving behavior on energy consumption and charging capacity. The simulation results show that at full CAV penetration rate, there are 62% reduction of average energy consumption of all types of vehicles and 10% increase of average energy stored per battery electric vehicle compared to full HVs case. This indicates that the eco-driving driving behavior has a positive impact on the energy stored powered by the DWPT system designed in this paper.

关键词： Coils Energy consumption Biological system modeling Batteries Computational modeling Layout Wireless power transfer

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Wheat Drought Assessment by Remote Sensing Imagery Using Unmanned Aerial Vehicle

Wheat Drought Assessment by Remote Sensing Imagery Using Unm...

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第37届中国控制会议

作者： Jinya Su Matthew Coombes Cunjia Liu Lei Guo Wen-Hua Chen Department of Aeronautical and Automotive Engineering Loughborough University Key Laboratory of Measurement and Control of Complex Systems of Engineering (Southeast University) Ministry of Education School of Electrical Engineering and Automation Beihang University

This work aims at evaluating the usability of remote sensing RGB imagery by an Unmanned Aerial Vehicle（UAV） in assessing wheat drought status. A UAV survey is conducted to collect high-resolution RGB imageries by using DJI S1000 for the experimental wheat fields of Gucheng town, Heibei Province, China. The soil moisture for different plots of the experimental filed is kept at an approximately constant level for the whole growing season in a well controlled environment, where field measurements are performed just after the UAV survey to obtain the soil water content for each plot. A machine learning based wheat drought assessment framework is proposed in this work. In the proposed framework, wheat pixels are first segmented from the soil background using the classical normalized excess green index（NEx G）. Rather than using pixel-wise classification,a pixel square of appropriate dimension is defined as the samples, based on which various features are extracted for the wheat pixels including statistical features and spectral index features. Different classification algorithms are experimented to identify a suitable one in terms of classification accuracy and computation time. It is discovered that Support Vector Machine with Gaussian kernel can obtain an accuracy over 90%, which demonstrates the usefulness of RGB imagery in wheat drought assessment.

关键词： Classification Remote sensing UAV imagery Wheat drought

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Iterative Learning Identification Using Quantized Observations 6

Iterative Learning Identification Using Quantized Observatio...

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2017 IEEE 6th Data Driven control and Learning systems Conference (DDCLS’17)

作者： Xuhui Bu Jian Liu Zhongsheng Hou School of Electrical Engineering & Automation Henan Polytechnic University Advanced Control Systems Lab. School of Electronics and Information EngineeringBeijing Jiaotong University

ISBN: (纸本)9781509054626

This paper develops a novel iterative learning parameter identification algorithm for a class of single parameter systems with multi-threshold quantized observations. The identification algorithm is constructed along the iteration axis and it can incorporate the parameter identification ability and the learning ability to deal with unknown time-varying parameters. Based on the recursive form of the estimation error along the iteration axis, it is proved that the convergence of parameter estimation can be guaranteed over the whole finite time interval. A numerical example is given to demonstrate the effectiveness of the algorithms.

关键词： Iterative Learning Parameter Identification Quantized Observations Time-varying Parameters

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Adaptive Dynamic Programming Based Decentralized Tracking control for Unknown Large-scale systems 36

Adaptive Dynamic Programming Based Decentralized Tracking Co...

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第36届中国控制会议

作者： Bo Zhao Derong Liu Yuanchun Li Qinglai Wei Ruizhuo Song The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Automation Guangdong University of Technology Department of Control Science and Engineering Changchun University of Technology School of Automation and Electrical Engineering University of Science and Technology Beijing

ISBN: (纸本)9781538629185

This paper investigates decentralized tracking control（DTC） problem for unknown large-scale systems via adaptive dynamic *** DTC consists of local desired control and local tracking error *** replacing the actual states of coupled subsystems in interconnection terms with their desired states,the norm-boundedness assumption can be *** on local neural network（NN） observers,unknown subsystems can be *** helps to obtain the local desired control with corresponding desired *** establishing a proper local cost function,the local tracking error control is derived via local critic NN and the identified input gain *** the entire error caused by replacement,identification and critic NN approximation,an adaptive robust term is added to construct the robust local cost function that reflects the entire error,regulation and control ***,the asymptotic stability can be guaranteed for the closed-loop tracking system via Lyapunov stability *** demonstrate the effectiveness of the proposed DTC,simulation on a hard spring connected parallel inverted pendulum system is given.

关键词： Adaptive dynamic programming Unknown large-scale systems Decentralized tracking control Neural networks Observer

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Exponential Stabilization of Nonlinear Parabolic PDE systems via Sampled-Data Fuzzy control Approach 36

Exponential Stabilization of Nonlinear Parabolic PDE Systems...

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第36届中国控制会议

作者： Zi-Peng Wang Huai-Ning Wu Han-Xiong Li School of Electrical Engineering University of Jinan Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical EngineeringBeihang University Department of Systems Engineering and Engineering Management City University of Hong Kong

ISBN: (纸本)9781538629185

This paper investigates the exponential stabilization problem of nonlinear parabolic partial differential equation(PDE)systems via sampled-data fuzzy control approach. Initially, the nonlinear PDE system is accurately represented by the TakagiSugeno(T-S) fuzzy PDE model. Then, based on the fuzzy PDE model, a novel time-dependent Lyapunov functional is used to design a sampled-data fuzzy controller such that the closed-loop fuzzy PDE system is exponentially stable with a given decay rate. The stabilization condition is presented in terms of a set of linear matrix inequalities(LMIs). Finally, simulation results on the temperature profile of a catalytic rod show that the proposed design method is effective.

关键词： Exponential Stability Sampled-Data control Fuzzy control Parabolic PDE systems Linear Matrix Inequality(LMI)

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New Grid for Particle Filtering of Multivariable Nonlinear Objects

New Grid for Particle Filtering of Multivariable Nonlinear O...

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Federated Conference on Computer Science and Information systems

作者： Piotr Kozierski Jacek Michalski Talar Sadalla Wojciech Giernacki Joanna Zietkiewicz Szymon Drgas Faculty of Computing Institute of Automation and Robotics Division of Signal Processing and Electronic Systems Poznan University of Technology Faculty of Electrical Engineering Institute of Control Robotics and Information Engineering Division of Control and Robotics Poznan University of Technology

ISBN: (纸本)9781538623718

In the paper a new grid (potentially linear, nonlinear and even semi-Markovian jump system) was presented. All transition and measurement functions were proposed. Moreover, the transition functions of two types were considered - dependent on one and many different state variables. Also 10 types of measurements were proposed for both nodal and branch cases. Based on the obtained results one can see, which measurement functions are "easy", and which are "hard" for state estimation task.

关键词： Measuring Function Particle filters grids Grid State variable Multivariable nonlinearity

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