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arXiv 2022年

作者： Cheng, Bin Lv, Yuezu Li, Zhongkui Duan, Zhisheng Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai200120 China Advanced Research Institute of Multidisciplinary Sciences Beijing Institute of Technology Beijing100081 China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing314000 China State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Peking University Beijing100871 China

This paper studies the consensus control problem faced with three essential demands, namely, discrete control updating for each agent, discrete-time communications among neighboring agents, and the fully distributed fashion of the controller implementation without requiring any global information of the whole network topology. Noting that the existing related results only meeting one or two demands at most are essentially not applicable, in this paper we establish a novel framework to solve the problem of fully distributed consensus with discrete communication and control. The first key point in this framework is the design of controllers that are only updated at discrete event instants and do not depend on global information by introducing time-varying gains inspired by the adaptive control technique. Another key point is the invention of novel dynamic triggering functions that are independent of relative information among neighboring agents. Under the established framework, we propose fully distributed state-feedback event-triggered protocols for undirected graphs and also further study the more complexed cases of output-feedback control and directed graphs. Finally, numerical examples are provided to verify the effectiveness of the proposed event-triggered protocols. Copyright © 2022, The Authors. All rights reserved.

关键词： Directed graphs

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The systematic error and the anomaly in the sensitivity and the probability of post-selection raised from the plural weak value

arXiv

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arXiv 2021年

作者： Huang, Jing-Hui Duan, Xue-Ying Wang, Guang-Jun Hu, Xiang-Yun Institute of Geophysics and Geomatics China University of Geosciences Wuhan430074 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China State Key Laboratory of Geological Processes and Mineral Resources China University of Geosciences Hubei Wuhan430074 China

Recently, weak value Aw derived in the pre- and post-selected weak measurement has been shown to be powerful in measuring minute physical effects. In principle, the decrease in the post-selection probability will increase the sensitivity. Besides, the sensitivity which characterizes the pointer position shift is proportional to the real part of Aw, and the sensitivity which characterizes the pointer shift in momentum space is proportional to the imaginary part of Aw. However, we find that the relationship between the post-selection probability and the sensitivity is true when Aw is a purely real number or a purely imaginary number. The plural Aw will lead to the abnormal behavior where the decrease in the post-selection probability reduce the sensitivity at certain pre- and post-selection. In addition, considering the device imperfections and the environmental instability in the WVA protocol, this anomaly raised from plural Aw will reduce the sensitivity and generate a systematic error of the measurement compared with the original scheme. Finally, three feasible methods are proposed to reduce these negative effects when the weak measurement inevitably changes into measurement with a plural weak value. © 2021, CC BY.

关键词： Probability

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Model analysis and experimental research on hydraulic high-speed impact system 8

Model analysis and experimental research on hydraulic high-s...

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8th IEEE International Conference on Fluid Power and Mechatronics, FPM 2019

作者： Wang, Shoukun Shi, Mingxin Chen, Zhihua Beijing Institute of Technolog Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing China Key Laborator Yof Servo Motion System Drive and Control Ministry of Industry and Information Technology School of Automation Beijing Institute of Technology Beijing China

ISBN: (数字)9781728103112

ISBN: (纸本)9781728103112

High-speed impact simulation test is an important test method to study the fatigue properties or limit parameters of materials. With the advantages of great impact energy, good program control and convenient test operation, hydraulic impact is widely used in high-speed impact field. A hydraulic high speed impact simulation system is designed in this paper, which uses high pressure accumulator to supply oil and converts hydraulic energy into impact energy through servo valve controlled cylinder system. This system can simulate dynamic change process of impact velocity and acceleration of projectile, and has impact angle adjustment and end buffer function. First, the composition and working principle of this hydraulic impact simulation system is introduced, as well as the analysis of the hydraulic impact mechanism. Second, the system dynamics model of servo valve controlled cylinder based on accumulator oil is built, and the simplified model and its basic characteristics are analyzed. Then, the Influences of various parameters in impact dynamic model on impact process are also discussed. Finally, the simulation system and physical prototype system of hydraulic impact is presented, the simulation and actual impact test data and corresponding analysis conclusions are also given. © 2019 IEEE.

关键词： Software testing

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Evasion strategies of a three-player lifeline game

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Science China(Information Sciences) 2018年第11期61卷 144-154页

作者： Fan ZHANG Wenzhong ZHA School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System Information Science Academy China Electronics Technology Group Corporation

This study examines a multi-player pursuit-evasion game, more specifically, a three-player lifeline game in a planar environment, where a single evader is tasked with reaching a lifeline prior to capture. A decomposition method based on an explicit policy is proposed to address the game qualitatively from two main aspects:(1) the evader's position distribution to guarantee winning the game(i.e., the escape zone),which is based on the premise of knowing the pursuers' positions initially, and(2) evasion strategies in the escape zone. First, this study decomposes the three-player lifeline game into two two-player sub-games and obtains an analytic expression of the escape zone by constructing a barrier, which is an integration of the solutions of two sub-games. This study then explicitly partitions the escape zone into several regions and derives an evasion strategy for each region. In particular, this study provides a resultant force method for the evader to balance the active goal of reaching the lifeline and the passive goal of avoiding capture. Finally,some examples from a lifeline game involving more than one pursuer are used to verify the effectiveness and scalability of the evasion strategies.

关键词： lifeline game three-player pursuit-evasion game barrier evasion strategy game of kind

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Coverage Path Planning Design of Mapping UAVs Based on Particle Swarm Optimization Algorithm

Coverage Path Planning Design of Mapping UAVs Based on Parti...

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第三十八届中国控制会议

作者： Shouqi Wang Yongqiang Bai Chao Zhou School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems

Mapping UAVs have played a more important role in regional mapping than ever before, and coverage path planning is an important part of mapping tasks. However, there are few studies on single-region path planning in complex polygonal region. In this paper, we proposed a method that searches the optimal yaw-angle and flight height of mapping UAVs based on particle swarm optimization algorithm. Compared with traditional algorithms such as cattle farming algorithm, there are less redundant coverage and turning, and the flight path planned by the algorithm in this paper is more reasonable and convenient for photographic processing.

关键词： mapping UAVs coverage path planning particle swarm optimization

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Gauss-Newton unrolled neural networks and data-driven priors for regularized PSSE with robustness

arXiv

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arXiv 2020年

作者： Yang, Qiuling Sadeghi, Alireza Wang, Gang Giannakis, Georgios B. Sun, Jian State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States

Renewable energy sources, elastic loads, and purposeful manipulation of meter readings challenge the monitoring and control of today’s power systems (PS). In this context, fast and robust state estimation (SE) is timely and of major importance to maintain a comprehensive view of the system in real time. Conventional PSSE solvers typically entail minimizing a nonlinear and nonconvex least-squares cost using e.g., the Gauss-Newton method. Those iterative solvers however, are sensitive to initialization, and may converge to local minima. To overcome these hurdles, the present paper adapts and leverages recent advances on image denoising to introduce a PSSE approach with a regularizer capturing a deep neural network (DNN) prior. For the resultant regularized PSSE objective, a "Gauss-Newton-type" alternating minimization solver is developed first. To accommodate real-time monitoring, a novel end-to-end DNN is constructed subsequently by unrolling the proposed alternating minimization solver. The deep PSSE architecture can further account for the power network topology through a graph neural network (GNN) based prior. To further endow the physics-based DNN with robustness against bad data, an adversarial DNN training method is put forth. Numerical tests using real load data on the IEEE 118-bus benchmark system showcase the improved estimation and robustness performance of the proposed scheme compared with several state-of-the-art alternatives. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep neural networks

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Wearable Human Foot Mechanical Energy Harvesting Device Based on Moving-coil Generator

Wearable Human Foot Mechanical Energy Harvesting Device Base...

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第三十八届中国控制会议

作者： Ning Ding Fang Deng Yeyun Cai Peng Gui Xinyu Fan School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems

In order to solve the problem of energy supply for smart wearable devices, this paper proposes a wearable human foot mechanical energy harvesting device based on moving-coil generator, and designs a moving-coil type power generation shoes prototype. Firstly, the human foot horizontal movement is analyzed based on the human gait model. Combined with the characteristics of wearable devices, we determine that mechanical energy harvesting device installed in the heel is the most effective. Secondly, the moving-coil generator is designed and the prototype of moving-coil type power shoes is made. Finally,using the movement test platform of the laboratory, We complete the comfort test and optimize the structure, as well as analyze the basic performance of the device, which has good high-frequency characteristics.

关键词： Wearable energy harvesting Moving-coil generator Mechanical energy Human body

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Online reinforcement learning control by direct heuristic dynamic programming: from time-driven to event-driven

arXiv

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arXiv 2020年

作者： Zhao, Qingtao Si, Jennie Sun, Jian Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing100081 China Department of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States

In this paper time-driven learning refers to the machine learning method that updates parameters in a prediction model continuously as new data arrives. Among existing approximate dynamic programming (ADP) and reinforcement learning (RL) algorithms, the direct heuristic dynamic programming (dHDP) has been shown an effective tool as demonstrated in solving several complex learning control problems. It continuously updates the control policy and the critic as system states continuously evolve. It is therefore desirable to prevent the time-driven dHDP from updating due to insignificant system event such as noise. Toward this goal, we propose a new event-driven dHDP. By constructing a Lyapunov function candidate, we prove the uniformly ultimately boundedness (UUB) of the system states and the weights in the critic and the control policy networks. Consequently we show the approximate control and cost-to-go function approaching Bellman optimality within a finite bound. We also illustrate how the event-driven dHDP algorithm works in comparison to the original time-driven dHDP. Copyright © 2020, The Authors. All rights reserved.

关键词： Learning algorithms

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Multilane Detection and Tracking Based on Binocular Vision Stixel World Estimation and IPM

Multilane Detection and Tracking Based on Binocular Vision S...

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第三十八届中国控制会议

作者： Jing Li Junzheng Wang Guangtao Cui Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology

Road detection is the basic component of many intelligent vehicle systems. In this paper, a robust multi-lane detection method based on binocular vision is proposed. First, a fast estimation technique of the Stixel World, which is the outside environment representation of stereo-vision, is developed. Taking advantage of the estimate for free space under the plane road hypothesis, the proposed method is robust against on-road obstacles when detecting lane markings. Then, the bird-view of the transitable area is obtained through Inverse Perspective Mapping(IPM) Transform;Steerable filter, parallel parabolas modal and RANdom SAmple Consensus(RANSAC) technique are introduced for multi-lane fitting. Experimental results in real urban driving situations indicate that our algorithm is robust under various conditions.

关键词： Multilane detection and tracking Binocular vision Stixel World RANSAC

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Parallel Structure of Six Wheel-legged Robot Model Predictive Tracking control based on Dynamic Model

Parallel Structure of Six Wheel-legged Robot Model Predictiv...

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Chinese Automation Congress (CAC)

作者： Bomeng Wang Junzheng Wang Shoukun Wang Jiehao Li Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

In the research of wheel-legged robots, trajectory tracking control is the inevitable requirement. In this paper, a trajectory tracking control scheme based on model predictive control for the parallel mechanism of six wheel-legged robot is proposed. A dynamic model was employed to reduce the amount of calculations for planning and control. In the model, the dynamic nonlinear constraints such as the tire slip rate and the roll caused by the lateral acceleration need to be considered. Finally, the control method is verified in the dynamic model. The simulation results show that all dynamic constraints can be maintained within a given interval and the control method has obvious tracking effect improvement.

关键词： Manganese

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