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SSRN 2024年

作者： Liu, Wenbo Kuang, Zhian Zhang, Yongcong Zhou, Bo He, Pengfei Li, Shihua School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Shanghai Friendess Electronic Technology Shanghai201100 China

Multi-robot task allocation is one of the most interesting multi-robot systems that have gained considerable attention due to various real-world applications. In this paper, we focus on a multi-robot task allocation problem where a set of industrial robots, which are installed on a gantry and have a limited working span, have to jointly perform a set of weld lines in large size. We present a mathematical model that captures the objective of minimizing the cycle time, i.e., the time required to complete a given set of weld lines. Due to the inherent difficulty of the problem, we propose an effective hybrid genetic algorithm to solve it. Because the robots are associated with a limited working span, the algorithm integrates a specific region division algorithm to divide the workpieces into a set of regions where the robots can reach all the weld lines in each region. It also incorporates a dedicated route-based crossover to generate promising offspring solutions and an effective neighborhoodbased local search procedu.e to improve each offspring solution as much as possible. Extensive experimental results on three benchmark instances show that the algorithm significantly outperforms reference methods. Additional experiments on real-world instances are presented to verify the algorithm’s effectiveness in solving the multi-robot task allocation problem with limited span. © 2024, The Authors. All rights reserved.

关键词： Industrial robots

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Hotspot detection of photovoltaic modules in infrared thermal image based on saliency analysis

Hotspot detection of photovoltaic modules in infrared therma...

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第34届中国控制与决策会议

作者： Yiye Wang Yu Shen Chenxi Li Kanjian Zhang Haikun Wei Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

With the increasing awareness of environmental protection,the solar photovoltaic(PV) industry has been developing dramatically in recent *** module is an important part of PV power generation *** all the defect types of PV modules,hotspots occur more frequently and cause more serious ***,it is necessary to detect *** approach is proposed using saliency analysis method for hotspot detection,combing the cognitive property about visual saliency and the temperature property of *** only does this approach not require manual threshold setting,but also it does not require a large number of learning *** approach can also achieve the defect diagnosis and hotspot location when compared with the electrical characterization *** infrared thermal(IRT)images trained in experiments are obtained using the thermographic camera FLIR Vue Pro with the unmanned aerial vehicle from a PV plant in Jiangsu,*** 135 IRT images are collected and 1020 PV modules are extracted from these *** have proved great accuracy and robustness when using the proposed method to detect hotspots.

关键词： Hotspot PV module IRT image Saliency analysis Graph

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Constraint-Following Based Adaptive Robust control for Underactuated Mechanical systems

Constraint-Following Based Adaptive Robust Control for Under...

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International Conference on control, Automation, Robotics and Vision (ICARCV)

作者： Cui Wei Ye-Hwa Chen Yanling Wei Institute of Intelligent Manufacturing Nanjing Tech University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Atlanta GA USA Key Laboratory of Measurement and Control of Complex System of Engineering School of Automation Southeast University Nanjing China

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

This paper introduces an adaptive robust control approach tailored for underactuated mechanical systems encountering matched and mismatched uncertainty, employing a constraint-following methodology. The control strategy unfolds in two phases: initially, a nominal control scheme is devised neglecting uncertainty and deviations in initial conditions from constraints. Subsequently, uncertainty is categorized into matched and mismatched components, ensuring that mismatched uncertainties remain unobservable. Leveraging the structural characteristics of the uncertainty bound, a novel segmented adaptive law is proposed and seamlessly integrated into the adaptive robust control framework. By employing the Lyapunov minimax approach, the method ensures uniform boundedness and uniform ultimate boundedness simultaneously, thereby ensuring approximate adherence to constraints for underactuated mechanical systems facing both matched and mismatched uncertainties alongside initial condition deviations.

关键词： Robust control Uncertainty Adaptive systems Costs Automation Nonlinear dynamical systems Mechanical systems Closed loop systems Robots

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Physics-Guided Human Motion Capture with Pose Probability Modeling

arXiv

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arXiv 2023年

作者： Ju, Jingyi Huang, Buzhen Zhu, Chen Li, Zhihao Wang, Yangang Southeast University China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Huawei Noah's Ark Lab Canada

Incorporating physics in human motion capture to avoid artifacts like floating, foot sliding, and ground penetration is a promising direction. Existing solutions always adopt kinematic results as reference motions, and the physics is treated as a postprocessing module. However, due to the depth ambiguity, monocular motion capture inevitably suffers from noises, and the noisy reference often leads to failure for physics-based tracking. To address the obstacles, our key-idea is to employ physics as denoising guidance in the reverse diffusion process to reconstruct physically plausible human motion from a modeled pose probability distribution. Specifically, we first train a latent gaussian model that encodes the uncertainty of 2D-to-3D lifting to facilitate reverse diffusion. Then, a physics module is constructed to track the motion sampled from the distribution. The discrepancies between the tracked motion and image observation are used to provide explicit guidance for the reverse diffusion model to refine the motion. With several iterations, the physics-based tracking and kinematic denoising promote each other to generate a physically plausible human motion. Experimental results show that our method outperforms previous physics-based methods in both joint accuracy and success rate. More information can be found at https://***/Me-Ditto/Physics-Guided-Mocap. Copyright © 2023, The Authors. All rights reserved.

关键词： Kinematics

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Data-Driven Distributed Robust Consensus Kalman Filtering for Sensor Networks

Data-Driven Distributed Robust Consensus Kalman Filtering fo...

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2021 China Automation Congress, CAC 2021

作者： Zhou, Ziai Wu, Hao Zhang, Ya School of Automation Southeast University Nanjing China 210096 Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China 210096

ISBN: (纸本)9781665426473

This paper mainly studies the distributed robust filtering problem for wireless sensor networks without knowing the variance of the driving noise and measuring noise. A distributed filtering algorithm based on leader-follower consensus strategy is developed. Firstly, from limited sampling data of noises, the empirical distribution of the noises which play a critical role in filtering is given. Secondly, by formulating the problem as a zero-sum game problem and using dynamic programming approach, an optimal distributed robust filtering policy with Wasserstein penalty for the leader is obtained. Then, by using an adaptively weighting average consensus protocol, the filtering algorithm for followers is given. The effectiveness of the proposed filter is demonstrated through simulations. © 2021 IEEE

关键词： Dynamic programming

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Inverse Reinforcement Learning Integrated Reinforcement Learning for Single Intersection Traffic Signal control

Inverse Reinforcement Learning Integrated Reinforcement Lear...

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International Conference on Industrial Artificial Intelligence (IAI)

作者： Shiyi Gu Tingting Zhang Ya Zhang School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China College of Command and Control Engineering Army Engineering University Nanjing China

Traffic Signal control (TSC) optimization is vital for efficient traffic flow in urban intersections. Recent research has explored the application of Reinforcement Learning (RL) agents to tackle TSC challenges. However, the selection of an appropriate reward function in RL agent training still relies on subjective judgment and experience. To address this issue, an Inverse Reinforcement Learning (IRL) integrated RL algorithm is proposed. In the IRL learning section, expert trajectory data are collected and analyzed by Relative Entropy IRL (REIRL). The latent reward of expert policy is reconstructed and utilized in RL agent training process. In the RL control section, a Double Dueling Deep Q Network is applied under a cycle control framework. As verified in simulations, the introduction of expert experience improves the performance of the RL agent to the expert level and concurrently enables robustness to expert policy noises.

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Fault Detection Method of Photovoltaic System Based on Power Change of Array 21

Fault Detection Method of Photovoltaic System Based on Power...

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Proceedings of the 2021 4th International Conference on Algorithms, Computing and Artificial Intelligence

作者： Chao Tan Chenxi Li Kanjian Zhang Haikun Wei Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University China

ISBN: (纸本)9781450385053

The fault detection of photovoltaic power generation system is of great significance in photovoltaic plant management. The conventional fault detection method of photovoltaic power system requires additional sensors, and the fault detection scheme needs to be redesigned if the parameters of the photovoltaic plant change. Therefore, for large photovoltaic plants, it is necessary to develop a method that does not require the use of external sensors or the detailed parameters of the photovoltaic plant. This paper proposes a photovoltaic system fault detection method based on photovoltaic array current and voltage data. This method does not require additional sensor data such as irradiance and temperature. The failure of photovoltaic system can be detected through the change of power, and the abnormal situation of photovoltaic power station can still be detected under cloudy and shaded conditions. The advantages of this method are that there is no need for complex and diverse sensor equipment, the calculation is simple and the fault detection ability is accurate. The experimental data of Padang Poverty Power Station of State Grid has been verified.

关键词： Sensorless Electrical data Power characteristics Photovoltaic System (PVS) Fault detection algorithm

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Moving-Window Integrated Physics-Data-Based Modeling of Lateral Dynamics

Moving-Window Integrated Physics-Data-Based Modeling of Late...

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American control Conference (ACC)

作者： Wenpeng Wei Guodong Yin Jinxiang Wang Tianyi He School of Mechanical Engineering Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China Department of Mechanical and Aerospace Engineering Utah State University Logan USA

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper proposes a moving-window Integrated Physics-Data-Based (IPDB) modeling method for the lateral dynamics of autonomous vehicles. The IPDB modeling method initiates from the fundamental physical principles of vehicle motions and express the nonlinear lateral dynamics directly by data snapshots in a moving window. Therefore, the IPDB model is physically interpretable and inherits adaptiveness of data-driven approaches. Specifically, the physics-based lateral dynamics are expressed into affine linear parameter-varying (LPV) formulation and system matrices can be successfully represented by the data snapshots in finite-length moving window without training or calibrations. After that, the CarSim simulations are conducted for data collection and to derive IPDB model. The data-efficient and online adaptive characteristics are validated by the data under several driving scenes. Simulation results confirm that the moving-window IPDB model only uses a small amount of data, but can exhibit great online modeling capability with strong adaptation and excellent model accuracy under varying driving scenarios.

关键词： Training Adaptation models Accuracy Computational modeling Dynamics Data models Mathematical models

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Joint Beam Management and SLAM for mmWave Communication systems

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IEEE Transactions on Communications 2023年第10期71卷 6162-6179页

作者： Que, Hang Yang, Jie Wen, Chao-Kai Xia, Shuqiang Li, Xiao Jin, Shi Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung80424 Taiwan Zte Corporation Shenzhen518055 China State Key Laboratory of Mobile Network and Mobile Multimedia Shenzhen518055 China Southeast University National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China

The millimeter-wave (mmWave) communication technology, which employs large-scale antenna arrays, enables inherent sensing capabilities. Simultaneous localization and mapping (SLAM) can utilize channel multipath angle estimates to realize integrated sensing and communication design in 6G communication systems. However, existing works have ignored the significant overhead required by the mmWave beam management when implementing SLAM with angle estimates. This study proposes a joint beam management and SLAM design that utilizes the strong coupling between the radio map and channel multipath for simultaneous beam management, localization, and mapping. In this approach, we first propose a hierarchical sweeping and sensing service design. The path angles are estimated in the hierarchical sweeping, enabling angle-based SLAM with the aid of an inertial measurement unit (IMU) to realize sensing service. Then, feature-aided tracking is proposed that utilizes prior angle information generated from the radio map and IMU. Finally, a switching module is introduced to enable flexible switching between hierarchical sweeping and feature-aided tracking. Simulations show that the proposed joint design can achieve sub-meter level localization and mapping accuracy (with an error © 1972-2012 IEEE.

关键词： Mapping

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Design of EL defect detection system for photovoltaic power station modules 4

Design of EL defect detection system for photovoltaic power ...

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2022 4th International Conference on Energy systems and Electrical Power, ICESEP 2022

作者： Li, Na Fan, Tao Yan, Shiqi Wu, Ziang State Grid Electronic Commerce Co.LTD Beijing China State Grid Corporation of China Beijing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China

In recent years, the photovoltaic power generation industry has been vigorously promoted and developed, while the solar cell as its core component may have micro-crack defects, which directly affect the power generation efficiency and stability of the photovoltaic system. Therefore, it is necessary to adopt a low-cost, efficient and flexible method to detect defects in solar cells. At present, most of the existing micro-cracks detection is carried out in the laboratory, and there is no EL micro-cracks detection in the actual photovoltaic power station. The main purpose of this paper is to design a set of EL defect detection system that can be used for actual photovoltaic power station modules, which is different from the traditional laboratory-level or module-level defect detection, and to carry the designed detection algorithm to the integrated device to operate. Experiments have shown that the system can perform real-time detection of photovoltaic module defects based on the string level, which improves the detection efficiency while saving time and cost, and shows good performance. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Crack detection

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