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第42届中国控制会议

作者： Huangyuwei Lu Zuo Wang Jiankun Sun Xi Xiao Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex systems of Engineering Ministry of Education Shenzhen Research Institute Southeast University School of Artificial Intelligence and Automation Huazhong University of Science and Technology Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration

To improve the disturbance rejection ability and repetitive tracking accuracy of manipulators,a composite iterative learning control(ILC) scheme via generalized proportional integral observer(GPIO) is proposed.A high-order polynomial is first employed to model the time-varying disturbances that include unmodeled dynamics,parameter uncertainties and load fluctuations.A GPIO is then designed to estimate the disturbances and high-order time *** introducing estimations into a PD-type ILC at each iteration,a composite control scheme is obtained,such that the undesirable influence of time-varying disturbances can be effectively attenuated in the repetitive tracking process of *** this paper,the rigorous stability analysis of the closed-loop system is presented to guarantee that the tracking error exponentially converges to zero as the iteration number tends to *** effectiveness of the proposed control scheme is finally verified by simulation results.

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Flexible Active Safety Motion control for Robotic Obstacle Avoidance: A CBF-Guided MPC Approach

arXiv

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arXiv 2024年

作者： Liu, Jinhao Yang, Jun Mao, Jianliang Zhu, Tianqi Xie, Qihang Li, Yimeng Wang, Xiangyu Li, Shihua The School of Automation The Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China Department of Aeronautical and Automotive Engineering Loughborough University LoughboroughLE11 3TU United Kingdom The College of Automation Engineering Shanghai University of Electric Power Shanghai200090 China

A flexible active safety motion (FASM) control approach is proposed for the avoidance of dynamic obstacles and the reference tracking in robot manipulators. The distinctive feature of the proposed method lies in its utilization of control barrier functions (CBF) to design flexible CBF-guided safety criteria (CBFSC) with dynamically optimized decay rates, thereby offering flexibility and active safety for robot manipulators in dynamic environments. First, discrete-time CBFs are employed to formulate the novel flexible CBFSC with dynamic decay rates for robot manipulators. Following that, the model predictive control (MPC) philosophy is applied, integrating flexible CBFSC as safety constraints into the receding-horizon optimization problem. Significantly, the decay rates of the designed CBFSC are incorporated as decision variables in the optimization problem, facilitating the dynamic enhancement of flexibility during the obstacle avoidance process. In particular, a novel cost function that integrates a penalty term is designed to dynamically adjust the safety margins of the CBFSC. Finally, experiments are conducted in various scenarios using a Universal Robots 5 (UR5) manipulator to validate the effectiveness of the proposed approach. Copyright © 2024, The Authors. All rights reserved.

关键词： Model predictive control

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Wheel Hub Automatic Production System Based on Industrial Robots 7

Wheel Hub Automatic Production System Based on Industrial Ro...

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2021 7th International Conference on Manufacturing Technology and Applied Materials, ICAMMT 2021

作者： Zhang, Bin Lu, Zongxue Wang, Qiang Cui, Shiyi Jia, Guangxin Yang, Jun School of Automation Southeast University 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Lianyungang Jari Automation CO. LTD. Lianyungang222006 China

In this thesis, a control system for a wheel hub machining line based on a Fanuc robot, which includes adopting Siemens 300PLC as the main control unit, performing wheel circumferential positioning and center correction based on vision technology, and controlling the machine tool to perform real-time tool compensation based on the measured data, is researched and designed to achieve fully automatic unmanned wheel processing. © Published under licence by IOP Publishing Ltd.

关键词： Wheels

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Research on Evolutionary Guiding Strategy for Self-organized Aggregates of Massive Flexible Resources

Research on Evolutionary Guiding Strategy for Self-organized...

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Advanced Electrical and Energy systems (AEES), International Conference on

作者： Tingfeng Mao Kaifeng Zhang Changwei Yin Xiaohui Pan Nan Ma Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing China Nanjing Power Supply Company of State Grid Jiangsu Electric Power Co. Ltd. Nanjing China

With the improvement of communication technology and the management of demand-side, more and more researches focus on the aggregation technology of flexible resources on the demand side. This paper proposes to build a self-organizing response framework in the scenario of massive resources, and resources can independently choose to join or exit the aggregates to participate in the regulation of grid active power balance. However, self-organizing aggregates cannot generate aggregation scenarios that accurately match the dynamic needs of the power grid during autonomous operation, so the grid needs to further guide the evolution of the aggregates. Firstly, the process and principle of realizing self-organization and evolution of resources in cyberspace are outlined. Then, the evolutionary driving sources of the self-organizing aggregates are analyzed to construct the evolutionary dynamics model framework from both the steady and the dynamic dimensions, and the data-driven modeling is carried out through the back propagation neural network to obtain the evolution law of resource self-organization. Finally, an iterative evolutionary guiding strategy based on price feedback is designed. The optimal guiding value of the market price cap is obtained through iteration under the expected aggregation scale target of the power grid, and also the dynamic evolution time of the aggregates is predicted to determine the timing of the release of the guiding strategy. The proposed strategy is constructed and tested on the NETLOGO resource self-organization simulation platform. The results show that the self-organizing aggregates can evolve to the expected state of power grid demand with high accuracy.

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DSTFormer: 3D Human Pose Estimation with a Dual-scale Spatial and Temporal Transformer Network

DSTFormer: 3D Human Pose Estimation with a Dual-scale Spatia...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Shaokun Zhang Xinde Li Chuanfei Hu Jianping Xu Huaping Liu School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Nanjing Center for Applied Mathematics Nanjing China Southeast University Shenzhen Research Institute Shenzhen China Science and Technology on Information Systems Engineering Laboratory Nanjing China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Recent transformer-based methods for estimating 3D human pose have gained widespread attention, achieving state-of-the-art results. Previous methods have primarily focused on capturing motion patterns of the human body at a single scale or cascading multiple scales, such as joints, bones, and body-parts. However, they are difficult to simultaneously capture spatial-temporal motion patterns of the human body at different scales due to the complex motion patterns. To address this issue, we propose Dual-scale Spatial and Temporal transFormer (DSTFormer), which can concurrently explore the spatial dependencies and temporal motion patterns of human joints and bones. Additionally, we introduce a Gcn-Spatial Transformer Block (GSTB), which introduces Graph Convolutional Networks (GCN) into transformer to enhance the exploitation of local relationships and global information between adjacent joints or bones. Extensive experiments are conducted on the Human3.6M benchmark dataset, and superior results are reported when comparing to other state-of-the-art methods. More remarkably, our model achieves to-date the best published performance, with P1 errors of 37.9 mm and 15.6 mm, respectively.

关键词： Solid modeling Three-dimensional displays Mechatronics Graph convolutional networks Computational modeling Pose estimation Transformers Bones Joints Robots

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Application of Integrated Sensing and Communication in Structural Health Monitoring

Application of Integrated Sensing and Communication in Struc...

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International Conference on Wireless and Optical Communications ( WOCC)

作者： Jie Yang Chao-Kai Wen Shi Jin Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung Taiwan National Mobile Communications Research Laboratory Southeast University Nanjing China

ISBN: (数字)9798331539658

ISBN: (纸本)9798331539665

Integrated sensing and communication (ISAC) is a primary goal in future cellular systems. Numerous researchers have explored how cellular systems can incorporate sensing capabilities in various use cases, such as intruder detection, monitoring, tracking, and collision avoidance. However, the potential of ISAC in structural health monitoring (SHM), which involves detecting slow and subtle changes in structures, remains unexplored. This study introduces a pioneering problem model and a solution framework for SHM using ISAC technology, employing reconfigurable intelligent surfaces (RIS) as reference points for monitoring building structures. Our method is inspired by the dynamic phase configuration of RIS to generate varying radio signals, which differ from background interference and thus facilitate the acquisition of precise radio measurements from the reference points. We conduct a theoretical analysis of these radio measurements through the lens of Fisher information. Our findings confirm that increasing observation time, adding more receivers, and optimizing RIS phases significantly enhance the position error bound (PEB) and orientation error bound (OEB) of the reference points, meeting the stringent accuracy requirements of SHM. Furthermore, we develop a Bayesian inference model to recognize structural states based on the calculated PEB and OEB, enabling the validation of detection probabilities of cellular systems in identifying damaged structural conditions. Our comprehensive theoretical and numerical analysis reveals the capability of ISAC to effectively detect millimeter-level deformations.

关键词： Wireless communication Wireless sensor networks Deformation Numerical analysis Buildings Receivers Reconfigurable intelligent surfaces Integrated sensing and communication Numerical models Monitoring

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Deep Learning-Based LOS and NLOS Parameters Estimation, Tracking, and Identification

Deep Learning-Based LOS and NLOS Parameters Estimation, Trac...

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IEEE International Conference on Communications in China Workshops (ICCC)

作者： Kai Chen Jun Wang Jie Yang Le Liang Chao-Kai Wen Shi Jin National Mobile Communications Research Laboratory Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung Taiwan

ISBN: (数字)9798350377675

ISBN: (纸本)9798350377682

Millimeter-wave (mmWave) communication systems have large bandwidths and, combined with large-scale antenna arrays and beamforming technology, facilitate higher resolution of angle and delay measurements. This, in turn, provides opportunities for integrated sensing and communication (ISAC). Accurate and reliable estimation of mmWave channel state information is crucial for ISAC. In this paper, we propose a deep learning-based method for estimating channel multipath parameters, tracking, and identifying line-of-sight (LOS) and non-line-of-sight (NLOS) paths. Specifically, we leverage a network named “you only look once (YOLO)”, a highly efficient object detection network in computer vision, to detect the angles of arrival (AOAs) and angles of departure (AODs) of multipaths from received radio frequency signals. Moreover, we use a tracking-by-detection algorithm, ByteTrack, to track the variation of each path's AOA and AOD under a mobile scenario. Thanks to these vision-based channel estimation approaches, we reveal that LOS and NLOS paths exhibit different trajectory properties, allowing us to precisely identify LOS and NLOS paths, a challenge originally in the context of ISAC. We validate the proposed estimation, tracking, and identification methods on real measurement data and demonstrate that the proposed estimation method shows better performance compared to existing methods.

关键词： Antenna measurements Computer vision Simultaneous localization and mapping Millimeter wave measurements Estimation Channel estimation Transforms Integrated sensing and communication Millimeter wave communication Antenna arrays

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Cooperative Resource Allocation for NOMA-MEC Multi-Cell Network

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IEEE Transactions on Vehicular Technology 2025年

作者： Cai, Yujin Zhang, Zaichen Huang, Yongming Yu, Wenwu Nie, Xiaokai Liu, Hongzhe Southeast University School of Mathematics Jiangsu Nanjing211189 China Southeast University National Mobile Communications Research Laboratory Nanjing211189 China Purple Mountain Laboratories Nanjing211111 China Southeast University School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Southeast University Shenzhen Research Institute Shenzhen518057 China

Integrating non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) enables IoT nodes to offload their complicated tasks to MEC servers. Most of the existing resource allocation schemes in NOMA-MEC networks are based on the centralized optimization framework, which may increase the communicational and computational burden on the central unit. In this paper, the NOMA-MEC multi-cell network without the central unit is considered. To minimize the task completion time and offloading cost, a joint optimization problem including sub-channel allocation, transmit power, offloaded proportions, computing frequencies of IoT nodes and MEC servers, and price of MEC resources is investigated. In order to tackle the formulated mixed integer nonlinear programming problem, a two-stage low-complexity distributed algorithm based on the cooperation of all base stations (BSs) is proposed. Specifically, in Stage 1, a distributed heuristic sub-channel allocation algorithm is designed based on the sub-channel gains. In Stage 2, with the obtained sub-channel allocation result, a cooperative distributed continuous variable optimization algorithm is devised based on the distributed optimization and alternating optimization methods. Numerical results demonstrate the convergence of the proposed two-stage algorithm for three interference cases. Besides, the impacts of system parameters and schemes on the network performance are analyzed. More importantly, the resource allocation time can be significantly shortened by employing the cooperation of BSs compared with the centralized algorithm © 1967-2012 IEEE.

关键词： Nonlinear programming

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Adaptive control Based on Neural Networks for an Uncertain 2-DOF Helicopter System With Input Deadzone and Output Constraints

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IEEE/CAA Journal of Automatica Sinica 2019年第3期6卷 807-815页

作者： Yuncheng Ouyang Lu Dong Lei Xue Changyin Sun IEEE the School of Automation and the Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University

In this paper, a study of control for an uncertain2-degree of freedom(DOF) helicopter system is given. The2-DOF helicopter is subject to input deadzone and output constraints. In order to cope with system uncertainties and input deadzone, the neural network technique is introduced because of its capability in approximation. In order to update the weights of the neural network, an adaptive control method is utilized to improve the system adaptability. Furthermore, the integral barrier Lyapunov function(IBLF) is adopt in control design to guarantee the condition of output constraints and boundedness of the corresponding tracking errors. The Lyapunov direct method is applied in the control design to analyze system stability and convergence. Finally, numerical simulations are conducted to prove the feasibility and effectiveness of the proposed control based on the model of Quanser's 2-DOF helicopter.

关键词： 2-degree of freedom (DOF) helicopter adaptive control input deadzone integral barrier Lyapunov function neural networks output constraints

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Adaptive Sliding Mode control for Force Tracking Using Nonlinear Observer

Adaptive Sliding Mode Control for Force Tracking Using Nonli...

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Chinese control and Decision Conference, CCDC

作者： Linyan Han Haibo Du Shihua Li Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing China School of Electrical Engineering and Automation Hefei University of Technology Hefei China

ISBN: (纸本)9781665478977

This paper focuses on the development of a control scheme capable of tracking contact forces explicitly. Specifically, the nonlinear observer, admittance control and adaptive sliding mode control are integrated into a single framework. When the force sensor is absent, a nonlinear observer, which serves as a reaction force observer, can be used to estimate the contact force. Furthermore, in order to track the force profile explicitly, admittance control is introduced to transform the desired contact force into the desired position signal. An adaptive sliding mode controller is designed to track the desired position and meanwhile compensate the estimation errors of contact forces caused by nonlinear observer. The stability of the whole system under the proposed controller can be guaranteed by the Lyapunov function. Finally, several simulations are reported to demonstrate the effectiveness of the proposed approach.

关键词： Service robots Simulation Force Transforms Observers Stability analysis Trajectory

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