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第三十八届中国控制会议

作者： Hu Xiaoyu Wang Shoukun State Key Laboratory of Intelligent Control and Decision of Complex System School of Automation Beijing Institute of Technology

Comparing to the commonly used hydraulic three-axial shaking tables, multi-degree of freedom shaking systems implemented by Stewart platform have the merits of being portable, easy to install and with high load capacity, but are not well studied because of the inherent nonlinearity and strong coupling of Stewart platform. In order to replicate multi-degree of freedom road acceleration spectrum on Stewart platform, analysis of the system was carried out. Firstly, the system structure was introduced and the linearized platform kinematic equations, at the equilibrium position, were inducted. The models of actuators that drive the platform were simplified and the principles of three variable controller(TVC) were deduced briefly. Finally, MATlab-Adams co-simulation environment was built to perform multi-degree of freedom road acceleration spectrum replication with TVC. The results show that it can reproduce high accuracy multi-degree of freedom road acceleration spectrum with TVC on Stewart platform.

关键词： Shaking table Stewart platform three variable controller

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Preface——Special Issue on New Directions in Nonlinear and Distributed control

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Journal of systems Science & complexity 2018年第1期31卷 1-3页

作者： LIU Tengfei XIN Bin JIANG Zhong-Ping State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang 110819 China School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing 100081 China Tandon School of Engineering New York University Brooklyn NY 11201 USA

Nonlinearity is ubiquitous in engineering and natural *** development of nonlinear control can be traced back to decades *** date,the research has reached the stage that emphasizes developing methodologies that can ha... 详细信息

关键词：控制问题非线性分布式工程应用程序电子物理自然系统生产线相互作用

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Large-scale 3D Semantic Mapping Using Stereo Vision

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International Journal of automation and computing 2018年第2期15卷 194-206页

作者： Yi Yang Fan Qiu Hao Li Lu Zhang Mei-Ling Wang Meng-Yin Fu School of Automation and National Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing 100081 China Nanjing University of Science and Technology Nanjing 210094 China

In recent years, there have been a lot of interests in incorporating semantics into simultaneous localization and mapping （SLAM） systems. This paper presents an approach to generate an outdoor large-scale 3D dense semantic map based on binocular stereo vision. The inputs to system are stereo color images from a moving vehicle. First, dense 3D space around the vehicle is constructed, and tile motion of camera is estimated by visual odometry. Meanwhile, semantic segmentation is performed through the deep learning technology online, and the semantic labels are also used to verify tim feature matching in visual odometry. These three processes calculate the motion, depth and semantic label of every pixel in the input views. Then, a voxel conditional random field （CRF） inference is introduced to fuse semantic labels to voxel. After that, we present a method to remove the moving objects by incorporating the semantic labels, which improves the motion segmentation accuracy. The last is to generate tile dense 3D semantic map of an urban environment from arbitrary long image sequence. We evaluate our approach on KITTI vision benchmark, and the results show that the proposed method is effective.

关键词： Semantic map stereo vision motion segmentation visual odometry simultaneous localization and mapping （SLAM）.

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Sequence impedance modeling of droop-controlled inverter

Sequence impedance modeling of droop-controlled inverter

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8th Renewable Power Generation Conference (RPG 2019)

作者： You Hu Jiajun Wang Bin Liu Zhen Li Xiangdong Liu School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing 100081 China

ISBN: (数字)9781839531248

ISBN: (纸本)9781839531255

The grid-connected three-phase inverter is an indispensable part of the microgrid. The droop control is widely used in parallel inverters for high reliability and flexibility. The output impedance of droop controlled inverters plays an vital role in its stability. However, the sequence impedance model of grid-connected inverter is currently based on the grid side converter with a single current loop control exdluding the low-frequency dynamics similar in doubly fed induction generators. Both the droop control and voltage loop control greatly affect the stability of inverter, specifically in the low frequency response. This paper proposes a sequence impedance model of inverter, which considers the droop control and voltage and current dual closed-loop control using the harmonic linearization method in the frequency domain. The accuracy of the model is verified through comparing the measurement impedance value in simulation with the impedance value calculated in the sequence impedance model. The influence of control method on system impedance is verified by showing the difference between the single loop controlled inverter and droop control inverter.

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Mobile Energy Transfer in Internet of Things

arXiv

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arXiv 2020年

作者： Zhang, Qingqing Wang, Gang Giannakis, Georgios B. Liu, Qingwen Chen, Jie College of Electronic and Information Engineering Tongji University Shanghai201800 China Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN 55455 United States State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Tongji University Shanghai200092 China

—Internet of things (IoT) is powering up smart cities by connecting all kinds of electronic devices. The power supply problem of IoT devices constitutes a major challenge in current IoT development, due to the poor battery endurance as well as the troublesome cable deployment. The wireless power transfer (WPT) technology has recently emerged as a promising solution. Yet, existing WPT advances cannot support free and mobile charging like Wi-Fi communications. To this end, the concept of mobile energy transfer (MET) is proposed, which relies critically on an resonant beam charging (RBC) technology. The adaptive (A) RBC technology builds on RBC, but aims at improving the charging efficiency by charging devices at device preferred current and voltage levels adaptively. A mobile ARBC scheme is developed relying on an adaptive source power control. Extensive numerical simulations using a 1,000mAh Li-ion battery show that the mobile ARBC outperforms simple charging schemes such as the constant power charging, the profile-adaptive charging, and the distance-adaptive charging in saving energy. Copyright © 2020, The Authors. All rights reserved.

关键词： Energy transfer

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Regret and Cumulative Constraint Violation Analysis for Distributed Online Constrained Convex Optimization

arXiv

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arXiv 2021年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Chai, Tianyou Johansson, Karl H. The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden The Digital Futures Stockholm10044 Sweden The Department of Control Science and Engineering College of Electronics and Information Engineering The Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore

This paper considers the distributed online convex optimization problem with time-varying constraints over a network of agents. This is a sequential decision making problem with two sequences of arbitrarily varying convex loss and constraint functions. At each round, each agent selects a decision from the decision set, and then only a portion of the loss function and a coordinate block of the constraint function at this round are privately revealed to this agent. The goal of the network is to minimize the network-wide loss accumulated over time. Two distributed online algorithms with full-information and bandit feedback are proposed. Both dynamic and static network regret bounds are analyzed for the proposed algorithms, and network cumulative constraint violation is used to measure constraint violation, which excludes the situation that strictly feasible constraints can compensate the effects of violated constraints. In particular, we show that the proposed algorithms achieve O(T max{κ,1-κ}) static network regret and O(T 1-κ/2) network cumulative constraint violation, where T is the time horizon and κ ∈ (0, 1) is a user-defined trade-off parameter. Moreover, if the loss functions are strongly convex, then the static network regret bound can be reduced to O(T κ). Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2021, The Authors. All rights reserved.

关键词： Economic and social effects

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Semi-autonomous greenhouse environment control by combining expert knowledge and machine learning

Semi-autonomous greenhouse environment control by combining ...

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Chinese automation Congress (CAC)

作者： Mengzhen Kang Yuchen Weng Haitong Pang Liangde Li Xing-Rong Fan Jing Hua Fangle Chang Xiujuan Wang Longhua Ma The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Ningbo Institute of Technology Zhejiang University Ningbo China The School of Computer Science and Information Engineering Chongqing Technology and Business University Chongqing China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao AgriTech Co. Ltd Qingdao Qingdao China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing Engineering Research Center of Intelligent Systems and Technology Beijing China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

The concept of "autonomous greenhouse" hints the automatic setting of control target, and giving orders on facilities to reach these targets (set point). Information and communication technologies are widely used, but how to integrate common sense or knowledge in decision-making is still challenging. Semi-autonomous greenhouse control is to set rules with joint advantages of experienced grower and powerful machinery, with the support of knowledge graph and semantic analysis. The contribution of each side is dependent on the intelligence level of computers, the availability of data, etc. In this work, the hybrid system between human and machinery is shown with the temperature control in greenhouse. The target is set mainly by expert knowledge, while the temperature controlled by vent opening is decided by an algorithm. Result shows that the target is better reached compared to that of the experience-based approach. This example shows the feasibility of human-machine hybrid intelligence system for greenhouse environment control. Although this approach is tested for temperature control, it can be extended to control multiple factors simultaneously (temperature, light intensity, humidity, etc.) by driving multiple facilities (heating, lightening, venting, etc.).

关键词： Green products Temperature measurement Monitoring Temperature sensors Vents Agriculture Temperature distribution

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Development of Sheet Palletizing Manipulator Based on Multi-link Mechanism

Research Square

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Research Square 2020年

作者： Chen, Zhihua Wang, Shoukun Liu, Quan Wang, Junzheng Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology School of Automation Beijing Institute of Technology Beijing100081 China New Energy Laboratory College of Mechanical and Electrical Engineering Beijing Information Science and Technology University Beijing100192 China

In view of the disadvantages of Traditional tandem joint type thin-plate palletizing robots using push-down adsorption sorting, such as moving path complexity, large occupied space, joint error stack and low end control precision, a novel multi-link mechanism thin-plate palletizing robot is developed. The kinematics analysis is carried out based on the analysis of the overall structure for the manipulator, a genetic algorithm based on the stroke speed ratio K, the transmission angle γ and the four-bar size is proposed to realize the optimal design of the four-link rocker arm mechanism. Secondly, a finite element based overall structure analysis method is proposed, which obtains the most affected part of the vibration process of a manipulator and performs load verification to prevent early warning and reference of faults caused by mechanical resonance. To solve the control problem of nonlinear strongly coupled dynamic systems, an iterative learning fuzzy adaptive control algorithm is proposed to achieve the smooth running of the manipulator and the high-precision tracking of the end centroid trajectory. The experimental results verify the feasibility and effectiveness of the proposed multi-link controllable thin-plate palletizing manipulator's overall structural design and iterative learning control method, which is well applied in practical engineering. © 2020, CC BY.

关键词： Manipulators

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Hybrid protocol for distributed non-differentiable extended monotropic optimization

Hybrid protocol for distributed non-differentiable extended ...

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International Conference on control and automation (ICCA)

作者： Xia Jiang Xianlin Zeng Jian Sun Jie Chen Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China Beijing Advanced Innovation Center for Intelligent Robots and Systems (Beijing Institute of Technology) Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology) Ministry of Education Beijing China School of Electronic and Information Engineering Tongji University Shanghai China

ISBN: (数字)9781728190938

ISBN: (纸本)9781728190945

This paper presents a hybrid protocol design for distributed non-differentiable extended monotropic optimization problems, which have various applications in large-scale optimization and evolutionary computation. The considered objective function is the sum of local non-differentiable objective functions, which are assigned to different agents in multi-agent networks, with local set constraints and affine equality constraints. Each agent can only access to its local non-differentiable objective function, local set constraint and equality constraint, and exchange information with its neighbors to obtain the global optimal solution. For this type of optimization problems, we propose a distributed state-dependent hybrid method over multi-agent networks. In addition, we properly design the jump map and jump set to improve the transient performance and accelerate the consensus process of existing distributed continuous-time methods. With invariance principle of hybrid dynamical systems, we prove that the proposed hybrid protocol converges to the global optimal solution. We verify that the proposed hybrid method has a good convergence property and transient performance through numerical experiments.

关键词： Optimization Protocols Linear programming Dynamical systems Heuristic algorithms Convergence Transient analysis

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Exponentially Convergent Algorithm Design for Constrained Distributed Optimization via Non-smooth Approach

arXiv

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arXiv 2020年

作者： Li, Weijian Zeng, Xianlin Liang, Shu Hong, Yiguang Department of Automation University of Science and Technology of China HefeiAnhui230027 China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Institute of Artificial Intelligence University of Science and Technology Beijing Beijing100083 China

We consider minimizing a sum of non-smooth objective functions with set constraints in a distributed manner. As to this problem, we propose a distributed algorithm with an exponential convergence rate for the first time. By the exact penalty method, we reformulate the problem equivalently as a standard distributed one without consensus constraints. Then we design a distributed projected subgradient algorithm with the help of differential inclusions. Furthermore, we show that the algorithm converges to the optimal solution exponentially for strongly convex objective functions. Copyright © 2020, The Authors. All rights reserved.

关键词： Constrained optimization

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