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第33届中国控制与决策会议

作者： Zhen Han Wei Wang Huijin Fan School of Automation Science and Electrical Engineering Beihang University Department of Control Science and Engineering Huazhong University of Science and Technology

In this paper,the distributed adaptive fault-tolerant formation control problem is investigated for a group of nonholonomic mobile robots(NMRs).The communication flow is described by a digraph and it is supposed that only a subset of the NMRs has direct access to the common desired ***,the actuators of each NMR may suffer from intermittent type of actuator *** estimate the unknown trajectory information and topology parameters,distributed estimators are proposed based on the neighboring available *** addition,estimators are also introduced to estimate the lower bounds of the actuator fault *** on the estimation values and Young's inequality,nonlinear damping terms are ***,a novel fault-tolerant control scheme is proposed by applying the adaptive backstepping *** is guaranteed that the formation errors will converge to an adjustable compact set and the control inputs are globally uniformly *** results validate the effectiveness of the proposed control scheme.

关键词： Fault-tolerant Distributed adaptive control Formation Nonholonomic mobile robots

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Riemannian Online Optimistic Algorithms with Dynamic Regret

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IEEE Transactions on Automatic control 2025年

作者： Wang, Xi Yuan, Deming Hong, Yiguang Hu, Zihao Wang, Lei Shi, Guodong University of New South Wales School of Electrical Engineering & Telecommunications SydneyNSW2052 Australia Nanjing University of Science and Technology School of Automation Nanjing210094 China Tongji University Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China Hong Kong University of Science and Technology Department of Mathematics Hong Kong Zhejiang University College of Control Science and Engineering Zhejiang 310058 China The University of Sydney Australian Center for Robotics School of Aerospace Mechanical and Mechatronic Engineering NSW2006 Australia

In this paper, we consider Riemannian online convex optimization with dynamic regret, which involves minimizing the cumulative loss difference between a learner's decisions and a sequence of adaptive decisions across dynamic environments over time on Riemannian manifolds. First, we propose Riemannian Online Optimistic Gradient Descent (R-OOGD), which extends the classical optimistic algorithms to Riemannian manifolds, requiring one gradient inquiry per round. We then propose Riemannian Adaptive Online Optimistic Gradient Descent (R-AOOGD) by incorporating the meta-expert framework into R-OOGD. We analyze the dynamic regret of R-OOGD and R-AOOGD in terms of the regularity of the sequence of cost functions and comparators. The dynamic regret bound matches the results in Euclidean space and with a scale adjustment of O(1+κ D2/√1-KD2) related to the sectional curvature lower bound κ, sectional curvature upper bound and feasible set diameter. Finally, we provide numerical experiments to illustrate the performance of the proposed algorithms. © 1963-2012 IEEE.

关键词： Optimization algorithms

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Performance Analysis and Design Optimization of Tubular Linear Oscillating Machine with Novel Compound Halbach Array

Performance Analysis and Design Optimization of Tubular Li...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Xiang, Pengjie Yan, Liang Wang, Tianyi Ge, Lijia Gerada, Chris Aboelhassan, Ahmed School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Science and Technology on Aircraft Control Lab Beijing100191 China Ningbo Institute of Technology Beihang University Ningbo315800 China University of Nottingham NottinghamNG7 2RD United Kingdom Alexandria1029 Egypt Key Laboratory of More Electric Aircraft Technology of Zhejiang Province University of Nottingham Ningbo China Ningbo315100 China

ISBN: (纸本)9789811966125

To achieve high force output and low mover mass of tubular linear oscillating machines simultaneously, we proposed a novel compound Halbach array consisting of the outer layer of quasi-Halbach array and inner layer of axial magnetized pattern. This magnetic pattern can completely removed the high-density back iron existed in conventional linear PM machines due to the much improvement of self-shielding effect. Thus, the mover mass can be greatly reduced and hence high dynamic performance can be obtain. Firstly, the mathematical models of the magnetic field and force output are established. And then, the key design parameters of the compound Halbach array are extracted from the analytical models. Besides, the response surfaces of force output and thrust fluctuation are established for investigating the coupling effect of these key design parameters on output characteristics. A multi-objective genetic optimization algorithm is performed to obtain structural parameters. Finally, the electromagnetic characteristics of the compound Halbach array are compared with conventional Halbach array to verify its merits. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electromagnetic shielding

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Concept, Principle, and Modeling of Driving Risk Entropy Based on Human-Vehicle-Road Coupling Model for Autonomous Vehicle

SSRN

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SSRN 2024年

作者： Gao, Hongbo Yang, Hanqing Zhu, Juping Su, Huiping Wang, Ning Xie, Liping Li, Keqiang Department of Automation University of Science and Technology of China Hefei230026 China Institute of Advanced Technology University of Science and Technology of China Hefei230088 China School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore Chongqing College of Mobile Communication Chongqing400044 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing100084 China

Driving risk entropy, based on entropy law, is an innovative concept proposed for intelligent driving systems. The concept deals with the driving risks caused by the human-vehicle-road system from the driving information obtained;however, driving risks are difficult to assess due to many influencing factors and great uncertainty. The risk entropy model of vehicles is visualized by introducing the concept of basic isotropic risk elliptic line (BIREL). Further incorporating the concept of information entropy, risk entropy models for vehicle interaction and vulnerable participants are established, and the risk entropy model for roads is developed using raster coordinates. Ultimately, a three-dimensional driving risk entropy model is constructed based on the human-vehicle-road coupling model, with appropriate weights assigned to each parameter through the DDPG algorithm. Experimental results demonstrate the effectiveness of the driving risk entropy model. © 2024, The Authors. All rights reserved.

关键词： Autonomous vehicles

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A Compatibility Evaluation Method for Substation Protection and Monitoring System Based on G1 Method and Expert Investigation 3

A Compatibility Evaluation Method for Substation Protection ...

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3rd International Conference on New Energy and Power engineering, ICNEPE 2023

作者： Xia, Hao Deng, Xiongyao Ma, Shizhong Yan, Yuxiang Xue, Ancheng Liu, Yu Shu, Zhihuai Chang, Naichao Li, Zhongqing Meng, Jiangwen Dou, Xuewei Wang, Shenqiang Wu, Fangying Fan, Chen State Key Laboratory of Alternate Electrical Power System with Renewable Energy Source North China Electric Power University Beijing China National Electric Power Dispatching and Control Center of State Grid Corporation of China Beijing China China Electric Power Research Institute Beijing China Beijing Sifang Engineering Co. Ltd Beijing China China Electric Power Research Institute Power Automation Department Nanjing China

ISBN: (纸本)9798350393224

In existing protection and monitoring system of substation(S-PMS), there are compatibility problems between hardware and software or between software-hardware combinations and systems, including differences in communication protocols between different manufacturers and differences in system adaptation. Compatibility issues have become a growing focus area for the power industry. This paper proposes a method to evaluates the compatibility of the protection and monitoring system of substation based on the G1 and expert investigation, for the existing or unbuilt substations. In detail, Firstly, according to the compatibility requirements of the substation protection and monitoring system, corresponding indicators are proposed and a comprehensive compatibility evaluation model is constructed. Secondly, based on the comprehensive evaluation model, the evaluation results of typical stations without domestic chips and optimized stations using domestic chips are compared to verify the feasibility of the proposed method. © 2023 IEEE.

关键词： Compatibility evaluation G1 method Protection and monitoring system

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Life Prediction of Rolling Bearing using Temporal Convolution Network and Attention Mechanism

Life Prediction of Rolling Bearing using Temporal Convolutio...

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Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS), CAA Symposium on

作者： GengWei Zhang YuXing Gu ZeHui Mao Bin Jiang Chengrui Liu College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China Beijing Institute of Control Engineering Beijing China

ISBN: (纸本)9781665401166

This paper focus on the life prediction of rolling bearing. In consideration of the traditional recurrent neural network (RNN) prediction method occupies a large memory and can not parallel processing data, a method combining temporal convolution network (TCN) with attention mechanism (TCN-Attention) is introduced to carry out life prediction. Convolution layers of TCN can obtain more information and reduce the memory occupancy compared with RNN under the same conditions, and the attention mechanism is used to extract the life related information to improve the prediction accuracy. Finally, experimental results show that the introduced TCN method can effectively predict the characteristics of vibration signals of rolling bearings, and the superiority of the introduced method is verified by comparing with the traditional RNN and long short-term memory (LSTM).

关键词： Vibrations Recurrent neural networks Convolution Simulation Fault detection Rolling bearings Predictive models

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Performance improvement of lithium-ion battery by pulse current

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Journal of Energy Chemistry 2020年第7期29卷 208-214,I0007页

作者： Shaoqing Zhu Chen Hu Ye Xu Yi Jin Jianglan Shui School of Mechanical Engineering and Automation Beihang UniversityBeijing 100191China State Key Laboratory of Operation and Control of Renewable Energy&Storage Systems China Electric Power Research InstituteBeijing 100192China School of Materials Science and Engineering Beihang UniversityBeijing 100191China

Periodically changed current is called pulse *** has been found that using the pulse current to charge/discharge lithium-ion batteries can improve the safety and cycle stability of the *** this short review,the mechanisms of pulse current improving the performance of lithium-ion batteries are summarized from four aspects:activation,warming up,fast charging and inhibition of lithium *** content may help us use the pulse current to improve the performance of lithium-ion batteries and further optimize pulse current technology.

关键词： Lithium ion battery Pulse current Activation Warming up Fast charging Lithium dendrites

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Accelerated Simulation of Non-Markovian Quantum Systems Using Quantum Trajectory

Accelerated Simulation of Non-Markovian Quantum Systems Usin...

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Chinese control Conference (CCC)

作者： Yanfang Wang Bo Yue Shibei Xue Department of Automation Shanghai Jiao Tong University Shanghai P. R. China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai P. R. China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai P. R. China

Quantum trajectory can be viewed as a numerical simulation method for wavefunctions which consume smaller memories compared to density matrices in master equations. In this paper, we adopt quantum trajectory to simulate the evolution of a non-Markovian quantum system modeled by an augmented system and further use parallel computing to improve efficiency. Compared to the Lindblad master equation solver in QuTiP, it can run more efficiently using less memory. In the example of a 8-spin-chain non-Markovian system, it only takes about 0.57% of the memory footprint and 4.12% of the runtime of the solver for the Lindblad master equation.

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Monitoring and Forecasting Quality Indicators of Predough Production in the Bakery Industry

Monitoring and Forecasting Quality Indicators of Predough Pr...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Nataliia Lutska Nataliia Zaiets Lidiia Vlasenko Andrii Zhyltsov dept. of Automation and Computer Technologies of Control Systems National University of Food Technologies Kyiv Ukraine dept. of Automation and Robotic Systems National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine dept. of Software Engineering and Cyber Security State University of Trade and Economics Kyiv Ukraine dept. of electromagnetic systems The Institute of Electrodynamics of the National Academy of Sciences of Ukraine Kyiv Ukraine

ISBN: (数字)9798350384499

ISBN: (纸本)9798350384505

The work demonstrates the process of developing a machine learning model for a system for monitoring and controlling the quality of predough at a bakery. This system will provide continuous analysis of the predough parameters, such as temperature, humidity, lifting force and titranic acidity, which will ensure timely detection of deviations in the quality of the predough and avoid production problems. In addition, it will help automate the quality control process and ensure the stability of production processes. Analysis and forecasting of dough parameters will improve the quality of produced bread or other bakery products. Management based also on the predicted values of technological indicators of the predough will allow the enterprise to avoid unnecessary costs of materials and energy and increase economic efficiency. As part of the study, seven machine learning models were created and reviewed, including three linear and four varieties of binary decision trees. An analysis of the best model - a regression decision tree - was carried out, confirming its effectiveness and the validity of the resulting hierarchical structure, in particular, the prediction of important indicators of predough with a high degree of reliability, which indicates its importance in practical applications in production. The created model can be used to monitor and control product quality in real time, allowing operators to quickly identify and correct any deviations in process performance. Also, by analyzing changes in the variables of the predough production process, it is possible to identify precursors of possible production accidents or deviations in product quality, which will allow timely measures to be taken to avoid them.

关键词： Force Process control Production Machine learning Quality control Humidity Predictive models Stability analysis Monitoring Thermal stability

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Spatial-Temporal-Rule-based Traffic Movement Status Interpretation at Intersections *

Spatial-Temporal-Rule-based Traffic Movement Status Interpre...

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Hanyang Zhuang Liyang Gao Yeqiang Qian Chunxiang Wang Ming Yang University of Michigan – Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai China Department of Automation Shanghai Jiao Tong University Shanghai Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

Traffic light is the most significant component of road transportation. Traffic lights control the traffic movement at intersections by allowing the movement of some lanes and forbidding that of the others to ensure safety and efficiency. It is important for intelligent vehicles to understand the meaning of traffic lights. Conventional research works on traffic light detection and tracking consider each light independently, so the occlusion of some lights may mislead the decision of the vehicle. Since all traffic lights at an intersection work together, it is more essential to understand the traffic movement status controlled by the traffic lights rather than the perception of a single light. Therefore, this paper proposes a spatial-temporal-rule-based framework to interpret the current traffic movement status and predict the next status. The spatial information, including position and class, is obtained by traffic light detection. The temporal information is perceived by the proposed topologic-feature-based tracking method. The rule information is recognized by combination of spatial and temporal information. A dual-view camera system consisting of a telephoto camera and a wide-angle camera is adopted to ensure long perception distance and wide coverage simultaneously. The successful tracking of traffic lights from 200 m to 10 m away provides enough data to recognize the phase-change rule, which leads to correct interpretation and prediction. A customized dataset was collected, and experiments were conducted to illustrate the capability of the proposed method.

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