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Annual Conference of Industrial Electronics Society

作者： Nannan Liu Tong Wang Jianmin Wang Yingda Fan School of Electronic and Information Engineering Ningbo University of Technology Ningbo China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin China Department of Computer Science University of Pittsburgh Pittsburgh USA

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

To minimize the disturbance of the Tunnel Boring Machine (TBM) cutterhead on the surrounding rock during the coal mine roadway excavation process and ensure that the cutterhead rotation speed achieves fast tracking performance with minimal overshoot, we propose a direct adaptive robust control method for the cutterhead rotation speed hydraulic system based on inversion design. This method considers the strong disturbances such as loads and motion affecting the cutterhead hydraulic drive system, as well as the uncertainties in the cutterhead model. We establish the nonlinear model of the cutterhead hydraulic drive system and employ virtual control to reduce the model order. Using Lyapunov functions, we ensure the stability of the entire system and derive the control law for the cutterhead rotation speed controller, along with parameter-adaptive laws acting as parameter estimators. We validate the effectiveness of the proposed control strategy through joint simulation using AMESim and Simulink. The results show that the designed cutterhead rotation speed controller achieves high tracking accuracy and good adaptability.

关键词： Robust control Adaptation models Uncertainty Tracking Software packages Hydraulic drives Tunneling Stability analysis Coal mining Load modeling

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Safe reinforcement learning task planning with uncertain duration and resource consumption in limited daytime for lunar rovers

Safe reinforcement learning task planning with uncertain dur...

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2024 IAF Space Operations Symposium at the 75th International Astronautical Congress, IAC 2024

作者： Lu, Siyao Xu, Rui Gao, Ai Li, Zhaoyu Liu, Jiamou Zhang, Libo Zhao, Zhijun Zhu, Shengying Li, Yuqiong School of Aerospace Engineering Beijing Institute of Technology 5th Zhongguancun South Street Haidian Distinct Beijing Beijing100081 China Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration Beijing Institute of Technology Ministry of Industry and Information Technology Beijing100081 China School of Computer Science University of Auckland 34 Princes Street Auckland1010 New Zealand Beijing Institute of Spacecraft Engineering Beijing Beijing100094 China Institute of Mechanics Chinese Academy of Sciences 15th North Fourth Ring West Road Haidian District Beijing100190 China

ISBN: (纸本)9798331312183

The International Lunar Research Station will be established near the south pole through advanced unmanned rovers at the beginning period. The south pole of the moon has short daytime, so the efficiency of remote control is inadequate. However, the duration and power resource usage of the lunar rover moving on the lunar surface remains uncertain because of different loading weight of collection and changes of terrain in moving. What’s more, a lunar rover needs to move back to the base before nighttime without sunlight to provide energy, while the whole time of working on the moon also needs optimization. We select to solve the planning problem with reinforcement learning (RL) due to its capability in tackling uncertainty and optimization. However, traditional reinforcement learning cannot guarantee safety with time uncertainty, resource uncertainty, and constraints due to the soft constraints in optimization. Therefore, we propose a new way through safe reinforcement learning of task planning and resource collection optimization among tasks with uncertain duration and resource collection. We consider a scenario of in-situ material utilization for the lunar base, where there are tasks of moving, charging, collecting, material delivering, and material receiving, all of which have uncertain duration in execution and every task must be done during the daytime except the charging. Resource collection is related to power consumption in moving so it will be decided according to the remaining power. We further propose an architecture on reinforcement learning to let rovers decide the next step instantaneously according to the expected task duration, the remaining time, and the remaining power. Maximizing the amount of material delivered is an optimization target in training while keeping the rovers safe to work only in the daytime without an empty battery. In our experiment, we intend that our way works well in the uncertainties, and it will lead the rover to finish tasks w

关键词： Reinforcement learning

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Predictive control based on Transformer as Surrogate Model for Cooling System Optimization in Data Center

Predictive Control based on Transformer as Surrogate Model f...

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2023 International Conference on Mobile Internet, Cloud Computing and Information Security, MICCIS 2023

作者： Ji, Jiezhou Yu, Donghui Yang, Dewang Shen, Xiao Liu, Haoran Zhao, Linqiang Wang, Tao Zeng, Yu Pan, Qiuhui Dalian University of Technology School of Mathematical Sciences Dalian China Dalian University of Technology School of Control Science and Engineering Dalian China Dalian University of Technology School of Computer Science and Technology Dalian China Quarkdata Technology Beijing China China Telecom Research Institute Beijing China

ISBN: (纸本)9798350300932

This paper develops a kind of Model Predictive control (MPC) based on the Transformer proxy model. Traditional MPC usually makes predictions via linear models which are unable to understand the interaction between various input variables. In this paper, we utilize the Transformer to approximate the nonlinear model, and capture the law of time series data. Specifically, we exploit the idea of dynamic programming to optimize the model to predict the cost of the trajectory, and recommend the control operation at each time point to determine the optimal strategy, and finally achieve the purpose of optimization. Experiments conducted on the data room energy-saving control problem demonstrated that, our Transformer based MPC model can predict the temperature change more accurately and is more robust to the field environment change. Moreover, compared with the previous Proportion Integration (PI) control, the MPC developed by us can make the temperature in the machine room is stable around 22°C, and the power consumption is reduced by 37.40%. © 2023 IEEE.

关键词： Model predictive control

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Minimum Time Escape from a Circular Region of a Dubins Car

Minimum Time Escape from a Circular Region of a Dubins Car

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IEEE National Conference on Aerospace and Electronics (NAECON)

作者： Isaac E. Weintraub Alexander Von Moll Meir N. Pachter Control Science Center Air Force Research Laboratory Wright-Patterson AFB OH Electrical and Computer Engineering Air Force Institute of Technology Wright-Patterson AFB OH

A turn-constrained evader strives to escape a circular region in minimum time.

ISBN: (数字)9798350367621

ISBN: (纸本)9798350367638

A turn-constrained evader strives to escape a circular region in minimum time.

关键词： Geometry Aerospace electronics Automobiles

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Throughput-oriented associated transaction assignment in sharding blockchains for IoT social data storage

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Digital Communications and Networks 2022年第6期8卷 885-899页

作者： Liping Tao Yang Lu Xu Ding Yuqi Fan Jung Yoon Kim School of Computer Science and Information Engineering Hefei University of TechnologyHefei230009China Engineering Research Center of Safety Critical Industrial Measurement and Control Technology Ministry of EducationHefei University of TechnologyHefei230009China Institute of Industry&Equipment Technology Hefei University of TechnologyHefei230009China Key Laboratory of Knowledge Engineering with Big Data(Hefei University of Technology) Ministry of EducationHefei230009China Graduate School of Game Gachon UniversitySeongnam-Si461-701South Korea

Blockchain is a viable solution to provide data integrity for the enormous volume of 5G IoT social data, while we need to break through the throughput bottleneck of blockchain. Sharding is a promising technology to solve the problem of low throughput in blockchains. However, cross-shard communication hinders the effective improvement of blockchain throughput. Therefore, it is critical to reasonably allocate transactions to different shards to improve blockchain throughput. Existing research on blockchain sharding mainly focuses on shards formation, configuration, and consensus, while ignoring the negative impact of cross-shard communication on blockchain throughput. Aiming to maximize the throughput of transaction processing, we study how to allocate blockchain transactions to shards in this paper. We propose an Associated Transaction assignment algorithm based on Closest Fit (ATCF). ATCF classifies associated transactions into transaction groups which are then assigned to different shards in the non-ascending order of transaction group sizes periodically. Within each epoch, ATCF tries to select a shard that can handle all the transactions for each transaction group. If there are multiple such shards, ATCF selects the shard with the remaining processing capacity closest to the number of transactions in the transaction group. When no such shard exists, ATCF chooses the shard with the largest remaining processing capacity for the transaction group. The transaction groups that cannot be completely processed within the current epoch will be allocated in the subsequent epochs. We prove that ATCF is a 2-approximation algorithm for the associated transaction assignment problem. Simulation results show that ATCF can effectively improve the blockchain throughput and reduce the number of cross-shard transactions.

关键词： IoT social data Blockchain Shar ding Associated transactions Transaction assi gnment

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Model Predictive control for Autonomous Driving: Comparing Kinematic and Dynamic Models of Tractor-Trailer Systems

Model Predictive Control for Autonomous Driving: Comparing K...

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International Conference on Intelligent Transportation

作者： Gustav Vallinder Jonas Mårtensson Pedro F. Lima Sriharsha Bhat Scania CV AB Södertälje Sweden Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

Investigations of kinematic and dynamic models of tractor-trailer systems have historically been performed for stability analysis or state estimation. In this work, we present and evaluate kinematic and dynamic tractor-trailer models for model predictive control (MPC). We show in open-loop simulations that a kinematic and a dynamic model are equivalent at low speeds and short discretization time steps. A zero speed singularity and stiff dynamics prevents the usage of the dynamic model in control design, where discretization time steps are longer. A method of discretization is proposed to resolve the low speed feasibility of the dynamic model. In closed-loop simulations, the real-time applicability of the kinematic and dynamic models in a nonlinear MPC is verified.

关键词： control design Optimal control Kinematics Predictive models Real-time systems Stability analysis State estimation Intelligent transportation systems Autonomous vehicles Predictive control

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Live Demo: E2P-Events to Polarization Reconstruction from PDAVIS Events

Live Demo: E2P-Events to Polarization Reconstruction from PD...

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2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Delbruck, Tobi Wang, Zuowen Mei, Haiyang Haessig, Germain Joubert, Damien Haque, Justin Chen, Yingkai Milde, Moritz B. Gruev, Viktor Univ. of Zurich and ETH Zurich Sensors Group Institute of Neuroinformatics Switzerland Center for Vision Automation & Control High-Performance Vision Systems AIT Austrian Institute of Technology Vienna Austria Western Sydney University Intl. Centre for Neuromorphic Systems The MARCS Institute Sydney Australia University of Illinois at Urbana-Champaign Dept. of Electrical and Computer Engineering UrbanaIL United States

This demonstration shows live operation of of PDAVIS polarization event camera reconstruction by the E2P DNN reported in the main CVPR conference paper Deep Polarization Reconstruction with PDAVIS Events (paper 9149 [... 详细信息

ISBN: (纸本)9798350302493

关键词： Polarization

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Robot path guidance algorithm based on compound collaborative filtering 6

Robot path guidance algorithm based on compound collaborativ...

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6th IEEE International Conference on Intelligent Computing and Signal Processing, ICSP 2021

作者： Liu, WenLin Cheng, JingLong Lu, XingHua Pan, YiFu Gao, YuNing Huali College Guangdong University of Technology Computer and Information Engineering Guangzhou China Institute of Computer Control Technology Huali College Guangdong University of Technology Guangzhou China

ISBN: (纸本)9780738143705

In order to improve the stability of control and path guidance of rigid-soft hybrid snake-like robot, a crawling path guidance method of rigid-soft hybrid snake-like robot based on composite collaborative filtering is proposed. The physical spatial grid distribution model of rigid-soft hybrid snake-like robot crawling is constructed, the SLAM guidance method is adopted to carry out grid regionalization matching in the obstacle avoidance process of rigid-soft hybrid snake-like robot, the optimization constraint parameters of obstacle avoidance path distribution of rigid-soft hybrid snake-like robot are established, and the path distribution characteristic variables in the obstacle avoidance process of rigid-soft hybrid snake-like robot are analyzed based on the kinematic characteristic analysis method. Parameter optimization design of rigid-soft hybrid snake-like robot crawling path guidance is carried out by local spatial feature distribution detection and recognition method, and optimization control is carried out by composite collaborative filtering algorithm. Adaptive inertial parameter optimization and accurate location are carried out by multi-sensor parameter positioning method. The simulation results show that this method has better adaptive optimization ability and higher robot positioning accuracy, which improves the obstacle avoidance and guidance ability of the rigid-soft hybrid snake robot. © 2021 IEEE.

关键词： Collaborative filtering

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Retrospect and prospect on integration of gain and phase for feedback stability analysis

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control Theory and Technology 2022年第4期20卷 555-558页

作者： Di Zhao Li Qiu Department of Control Science and Engineering&Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 201804China Department of Electronic and Computer Engineering The Hong Kong University of Science and TechnologyClear Water BayKowloonHong KongChina Guangzhou HKUST Fok Ying Tung Research Insititute Nansha DistrictGuangzhou 511458GuangdongChina

In this paper,we review existing approaches to integrating small gain and small phase analysis for feedback stability of dynamical systems,and give a brief outlook for possible future directions in exploring this *** gain analysis has been very successful and popular in control theory since 1960s,while the small phase analysis for multiple-input-multiple-output systems has not been well understood until recently and is now gradually taking ***,there have been attempts to analyzing feedback stability via the integration of gain and phase information over decades,including the combination of small gain with positive realness as well as that with negative *** combinations can be subsumed into a recently proposed framework for gain-phase integration,which brings in new geometrical methods and also sheds new lights on several future directions.

关键词： Small gain Small phase Passivity Positive real Negative imaginary Davis-Wielandt shell

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Distributed State Estimation Under Multi-step Random Transmission Delay and Packet Loss

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IEEE Transactions on Aerospace and Electronic Systems 2025年

作者： Dai, Hongyun Fu, Junjie Duan, Peihu Wen, GuanGhui Huang, Tingwen Southeast University School of Mathematics Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm Sweden Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

This paper investigates the problem of underwater distributed state estimation with multi-step random communication delay and packet loss. Since underwater communication adopts acoustic communication, the information transmission speed is relatively slow, and multi-step delay and packet loss situations are frequently encountered. Based on the hybrid consensus filtering algorithm and a proper buffer setting, a distributed Kalman filtering algorithm is proposed, which can deal with possible multistep random time delay and packet loss. A sufficient condition for the filtering stability is rigorously established. In addition, the state estimation problem for an uncertain target model in underwater environments is addressed by combining the Interacting Multiple Model method. Finally, numerical simulations validate the effectiveness of the proposed algorithm and the accuracy of the conclusions, while also demonstrating that this method achieves a 13.9% reduction in the cross-secenario composite RMSE compared to similar buffer-based approaches, further emphasizing its superiority. © 1965-2011 IEEE.

关键词： Convergence of numerical methods

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