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arXiv 2019年

作者： Xu, Yong Zhang, Hao Li, Yongge Zhou, Kuang Liu, Qi Kurths, Jürgen Department of Applied Mathematics Northwestern Polytechnical University Xi’an710072 China MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University Xi’an710072 China Department of Engineering Mechanics Northwestern Polytechnical University Xi’an710072 China Center for Mathematical Sciences School of Mathematics and Statistics HuazhongUniversity of Science and Technology Wuhan430074 China Potsdam Institute for Climate Impact Research Potsdam14412 Germany Department of Physics Humboldt University Berlin Berlin12489 Germany

The probability density function of stochastic differential equations is governed by the Fokker-Planck (FP) equation. A novel machine learning method is developed to solve the general FP equations based on deep neural networks. The proposed algorithm does not require any interpolation and coordinate transformation, which is different from the traditional numercial methods. The main novelty of this paper is that penalty factors are introduced to overcome the local optimization for the deep learning approach, and the corresponding setting rules are given. Meanwhile, we consider a normalization condition as a supervision condition to effectively avoid that the trial solution is zero. Several numerical examples are presented to illustrate performances of the proposed algorithm, including one- and two-dimensional systems. All the results suggest that the deep learning is quite feasible and effective to calculate the FP equation. Further, influences of the number of hidden layers, the penalty factors, and the optimization algorithm are discussed in detail. These results indicate that the performances of the machine learning technique can be improved through constructing the neural networks appropriately. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

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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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Interdependent order allocation in the two-echelon supply chain using agent-based negotiation 36

Interdependent order allocation in the two-echelon supply ch...

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第36届中国控制会议

作者： Jian Wang Huimin Miao System Engineering Institute School of AutomationHuazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Hubei Province Key Laboratory of Systems Science in Metallurgical Process Wuhan University of Science and Technology

ISBN: (纸本)9781538629185

Nowadays,many researches study the negotiation-based order allocation problem in the supply chain environment,aiming to improve the efficiency of the allocation and the profits of the supply chain *** competition and cooperation in supplier’s side are mainly addressed because of independent *** this paper,we analyze an interdependent order allocation problem in a two-echelon supply *** supply chain consists of a manufacturer echelon and a supplier *** to the interdependence,both the competition and cooperation in the manufacturer echelon are *** agent-based negotiation algorithm is developed to support the order allocation process and the conflicts *** show in experiments that orders under various supply chain contexts can be successfully allocated through the algorithm.

关键词： Supply chain system order allocation agent-based negotiation

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Adaptive-Learning-Based H∞ Optimal Tracking control Design for a Class of Constrained Nonlinear systems

Adaptive-Learning-Based H∞ Optimal Tracking Control Design ...

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第37届中国控制会议

作者： Jiaxu Hou Ding Wang Derong Liu School of Automation and Electrical Engineering University of Science and Technology Beijing 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 Automation Guangdong University of Technology

This paper, considering constrained inputs, focuses on designing the optimal controller for discrete-time H∞ tracking control problems. The neural-network-based iterative learning algorithm is deemed to be an excellent method to work. The iterative heuristic dynamic programming algorithm is employed for developing the formulated regulation of the tracking error. Strict convergence guarantees are given to support the optimality of the adaptive algorithm. A neural-network-based training scheme is adopted to implement the learning algorithm and stabilize the system in the optimal manner. Two numerical examples are provided to illustrate the applicability and good performance of the designed tracking control scheme.

关键词： Adaptive dynamic programming H∞ tracking control constraints convergence proof

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An SNR-Adaptive Relaying Algorithm for Multi-Antenna Cooperative Networks

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China Communications 2017年第10期14卷 228-236页

作者： Shuangshuang Han Peng Zhang Feijin Shi Fei-Yue Wang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of SciencesBeijing China Qingdao Academy of Intelligent Industries Qingdao Shandong Province China The School of Computer Engineering Weifang University Shandong P. R. China Communications Headquarters Ministry of Foreign Affairs of the People's Republic of China Beijing China Research Center of Computational Experiments and Parallel Systems The National University of Defense Technology Changsha China

Multiple-input multiple-output(MIMO) and cooperative communications have been attracted great attention for the improvements of communication capacity, power consumption, and transmission coverage. The conventional fixed relaying protocols, amplify-and-forward(AF) and decode-and-forward(DF), have their own advantages and disadvantages, i.e. AF performs better than DF for low signal-to-noise ratio(SNR) region, while the reverse is true for high SNR region. Therefore, this paper proposes an SNR-adaptive forward(SAF) relaying scheme obtaining the advantages of both AF and DF. Furthermore, the proposed SAF does not need to switch between AF and DF when SNR changes. The main idea is to adaptively derive the soft information at the cooperative relay nodes based on the information of the received signal and the SNR. Besides, based on the theoretical analysis and the simulation results, it is affirmed that the proposed SAF achieves superior performance than both AF and DF for all SNRs. Moreover, the performance gain would be improved with the increasing number of parallel cooperative relay nodes.

关键词： MIMO SNR SNR-adaptive forward multi-antenna

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Precise planar motion measurement of a swimming multi-joint robotic fish

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Science China(Information Sciences) 2016年第9期59卷 183-197页

作者： Jun YUAN Junzhi YU Zhengxing WU Min TAN State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

This paper presents a method for planar motion measurement of a swimming multi-joint robotic fish. The motion of the robotic fish is captured via image sequences and a proposed tracking scheme is employed to continuously detect and track the robotic fish. The tracking scheme initially acquires a rough scope of the robotic fish and thereafter precisely locates it. Historical motion information is utilized to determine the rough scope, which can speed up the tracking process and avoid possible ambient interference. A combination of adaptive bilateral filtering and k-means clustering is then applied to segment out color markers accurately. The pose of the robotic fish is calculated in accordance with the centers of these markers. Further, we address the problem of time synchronization between the on-board motion control system of the robotic fish and the motion measurement system. To the best of our knowledge, this problem has not been tackled in previous research on robotic fish. With information about both the multi-link structure and motion law of the robotic fish, we convert the problem to a nonlinear optimization problem, which we then solve using the particle swarm optimization(PSO) algorithm. Further, smoothing splines are adopted to fit curves of poses versus time, in order to obtain a continuous motion state and alleviate the impact of noise. Velocity is acquired via a temporal derivative operation. The results of experiments conducted verify the efficacy of the proposed method.

关键词： motion measurement robotic fish time synchronization visual tracking localization

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Terrain Estimation and Strategy for Quadruped Robot Body Posture and COG Adjustment 28

Terrain Estimation and Strategy for Quadruped Robot Body Pos...

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第28届中国控制与决策会议

作者： HE Yudong WANG Junzheng KE Xianfeng WANG Shoukun Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781467397155

Quadruped robot has gained its popularity due to the adaptation ability of rough *** improve the walking stability and balance of quadrupeds,separate static walking methods are discussed based on specific known *** some unknown terrains,a uniform terrain model is established in this paper.A fuzzy logic based terrain estimation method is then proposed to estimate the terrain *** on the criterion of maximum working space,a body posture and center of gravity(COG) position adjusting strategy is proposed,and a method to adjust the posture and COG position is derived based on the kinematic *** show that the proposed methods can deal with different terrains and body posture and COG position can be tuned according to the terrain.

关键词： Quadruped Robots Terrain Estimation Body Posture and COG adjustment

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Non-contact transportation and rotation of micro objects by vibrating glass needle circularly under water

Non-contact transportation and rotation of micro objects by ...

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2017 IEEE International Conference on Robotics and Automation, ICRA 2017

作者： Liu, Xiaoming Kojima, Masaru Shi, Qing Wang, Huaping Sun, Tao Mae, Yasushi Huang, Qiang Arai, Tatsuo Fukuda, Toshio Intelligent Robotics Institute School of Mechatronical Engineering Key Laboratory of Biomimetic Robots and Systems Ministry of Education Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing100081 China Department of Systems Innovation Osaka University 1-3 Machikaneyama Toyonaka Osaka560-8531 Japan Faculty of Science and Engineering Meijo University 1-501 Shiogamaguchi Tenpaku-ku Nagoya468-8502 Japan

ISBN: (纸本)9781509046331

In micromanipulation, lots of methods have been developed to manipulate objects in microscale. However, few of them can be applied in both the transportation and the rotation of the micro objects. In this paper, we present a novel method to realize the non-contact transportation and rotation of the micro objects based on the vibration-induced swirl flow. A piezo actuator is set between the glass needle and a metal rod. The sine wave with controlled frequency and amplitude is input into the piezo actuator to drive the glass needle to move circularly, which is caused by resonance of the actuator and the metal rod. We place the glass needle under water and keep a limited distance to the bottom. The circular vibration of the glass needle can generate a swirl flow and low pressure around it. The low pressure can trap and transport the micro objects vertically to the glass needle, and the swirl flow can rotate the objects continuously. Finally, we realize the trap and rotation of micro object with only one piezo actuator. Experiments of transportation and rotation of microbeads are carried out, and the results demonstrate it is a simple, low-cost, effective micromanipulation method. © 2017 IEEE.

关键词： Needles

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Nonlinear robust control design for SSSC to improve damping oscillations and transient stability of power system 36

Nonlinear robust control design for SSSC to improve damping ...

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第36届中国控制会议

作者： Bangjun Lei Xiang Wu Shumin Fei Key Laboratory of power big data of Guizhou Province College of Electrical and Information EngineeringGuizhou Institute of Technology School of Mathematical Sciences Guizhou Normal University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

ISBN: (纸本)9781538629185

In this article, a nonlinear robust（NR） control is designed for static synchronous series compensator（SSSC） to improve transient stability and oscillation damping of power system. By taking the parameter deviations, external disturbances and unmodeled dynamics into account, the nonlinear dynamic model of SSSC can be changed into a Hamiltonian structure with the help of coordinate transformation. Based on the Hamiltonian structure of SSSC, a nonlinear robust control is designed for SSSC. Numerical simulation results on the two-area four-machine power system demonstrate the robustness and effectiveness of the proposed nonlinear robust control in comparison with the direct feedback linearization（FL） control. The study results show that the nonlinear robust control has better performance than the FL control.

关键词： SSSC nonlinear robust control Hamiltonian function method oscillations damping transient stability

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DC-DC Buck-Boost Converters with Unknown CPL: An Adaptive PBC

DC-DC Buck-Boost Converters with Unknown CPL: An Adaptive PB...

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2018 Annual American control Conference, ACC 2018

作者： He, Wei Abraham Soriano-Rangel, Carlos Ortega, Romeo Astolfi, Alessandro Mancilla-David, Fernando Li, Shihua Ministry of Education School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing210096 China University of Colorado Denver Department of Electrical Engineering Denver United States Laboratoire des Signaux et Systemes Supelec Plateau du Moulon Gif-sur-Yvette91192 France Department of Electrical and Electronic Engineering Imperial College London LondonSW72AZ United Kingdom

ISBN: (纸本)9781538654286

We develop in this paper an adaptive passivity-based controller for output voltage regulation of DC-DC buck-boost converter with unknown constant power load. This control problem is theoretically challenging since the average model of the converter is a bilinear second order system that, due to the presence of the constant power load, is non-minimum phase with respect to both states. A solution to the problem was recently reported in [9], however, the resulting control law is extremely complicated to be of practical interest. The aim of the paper is to design a novel, significantly simpler, controller that can be easily implemented in applications. The key modifications introduced in the new design are the use of a change of coordinates and a partial linearization that transform this system into a cascade form, to which an adaptive energy-shaping controller is applied. Another merit of the designed control law, besides its simplicity, lies in that it is amenable for the addition of an outer-loop PI that improves its transient and disturbance rejection performances. Simulations and experimental results are provided to assess the improved performance of the proposed controller. © 2018 AACC.

关键词： Mathematical model Load modeling Asymptotic stability Voltage control Adaptation models Adaptive systems Stability analysis"

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