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Data Driven control and Learning systems (DDCLS)

作者： Baozeng Fu Qingzhi Wang Yongchao Liu Shandong Key Laboratory of Industrial Control Technology School of Automation Qingdao University Qingdao China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China

The stabilization of Port-controlled Hamiltonian (PCH) systems under exogenous disturbances by designing a compensation control approach is studied in the paper. Firstly, a baseline feedback control is proposed utilizing the damping injection method. To estimate disturbances, then a novel exogenous disturbance observer is constructed, based on which a feedforward compensation control is developed. Next, a composite control law is proposed based on the feedforward compensation and the feedback control. For the Hamiltonian system, an asymptotic stability analysis is followed finally. The feasibility of the compensation control strategy is revealed by a numerical simulation example.

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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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An optimal trajectory planning algorithm for T-shaped acceleration curve with non-zero acceleration at the beginning and end

An optimal trajectory planning algorithm for T-shaped accele...

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Chinese automation Congress (CAC)

作者： Yongxu Luo Gan Yahui Dai Xianzhong School of Automation Southeast University Key Laboratorty of Measurement and Control of Complex Systems of Engineering Ministry NanJing China

In order to solve the problem that T-type trajectory planning curve can not completely replace polynomial trajectory planning,this paper proposes an S-type programming algorithm based on the optimization algorithm with T-type acceleration. The algorithm solves the complex and cumbersome problem of time planning of T-shaped acceleration and deceleration curve with non-zero acceleration and velocity at the beginning and end. Taking into account the characteristics of fast acceleration of trajectory planning curve, it can not only solve the case where the initial and end velocities are not zero, but also solve the case where the initial and end accelerations are not zero. The algorithm is based on the analysis of the characteristics of acceleration stage, constant speed stage and deceleration stage. When the highest speed of the curve is determined, the time of all speed segments is also determined. The concept of maximum reachable speed of trajectory is proposed. The complex multivariate nonlinear programming is transformed into a single convex function. The algorithm is simplified by using the symmetry of the variation forms in acceleration stage and deceleration stage. The maximum achievable velocity is solved by dichotomy, Newton iterative method and gradient descent method. The experiment shows that the solving efficiency of Newton iterative method is 40% higher than that of dichotomy method. Compared with the quintic polynomial programming algorithm, the overall planning time is reduced by 9.6% and the tracking error is reduced by 15.9%.

关键词： Trajectory planning Tracking Motion segmentation Optimization methods Linearity Programming Trajectory

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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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Task-Centered Heterogeneous Multi-Robot Cooperative Task Allocation and Planning: An Welding Case Study

SSRN

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SSRN 2024年

作者： Liu, Wenbo Kuang, Zhian Zhang, Yongcong Zhou, Bo Li, Shihua School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Shanghai Friendess Electronic Technology Shanghai201100 China

In this article, the complicated task assignment, scheduling and planning of heterogeneous multi-robot welding process are studied. Firstly, for large-scaled tasks that involve heterogeneous multi-robot task allocation under different internal and external constraints, the traditional multi-robot task allocation (MRTA) framework is extended to a novel and unified heterogeneous multi-robot task allocation (H MRTA)***,robotsofdifferentconfigurations (including manipulators, positioners, gantries) are treated as unified robots. Secondly, taking into account constraints such as reachability, collision avoidance, kinematic and dynamic process constraints, the optimization model based on H-MRTA framework is established. The optimization objectives are formulated by combining the total execution time and load balance between robots. Then, a hierarchical optimization algorithm(TCO-HMRTA) is proposed to solve the H-MRTA problem with decoupled two-layer optimization sub-problems : task space segmentation subproblem and multi-robot path planning subproblem. For the task space segmentation subproblem, a task-centered optimization model is established, which aims to balance the workload among robots, considering the competition and cooperation between robots. For the multi-robot path planning problem, multiple process constraints are considered and the total working time is minimized as the objective function. Finally, The effectiveness of the optimization algorithm is verified by a case study on the welding task of a large plate element in a ship hull. Compared to two other state-of-the-art algorithms, TCO-HMRTA can save more than 50% of the waiting time and 10%-20% of the execution time, which demonstrates the effectiveness and feasibility of the hierarchical optimization-based task allocation algorithm for complicated heterogeneous multi-robots. © 2024, The Authors. All rights reserved.

关键词： Industrial robots

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Multi-object Tracking by Detection and Query: an efficient end-to-end manner

arXiv

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arXiv 2024年

作者： Jia, Shukun Cao, Yichao Yang, Feng Lu, Xin Lu, Xiaobo School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China School of Instrument Science and Engineering Southeast University Nanjing210096 China

Multi-object tracking is advancing through two dominant paradigms: traditional tracking by detection and newly emerging tracking by query. In this work, we fuse them together and propose the tracking-by-detection-and-query paradigm, which is achieved by a Learnable Associator. Specifically, the basic information interaction module and the content-position alignment module are proposed for thorough information Interaction among object queries. Tracking results are directly Decoded from these queries. Hence, we name the method as LAID. Compared to tracking-by-query models, LAID achieves competitive tracking accuracy with notably higher training efficiency. With regard to tracking-by-detection methods, experimental results on DanceTrack show that LAID significantly surpasses the state-of-the-art heuristic method by 3.9% on HOTA metric and 6.1% on IDF1 metric. On SportsMOT, LAID also achieves the best score on HOTA metric. By holding low training cost, strong tracking capabilities, and an elegant end-to-end approach all at once, LAID presents a forward-looking direction for the field. Copyright © 2024, The Authors. All rights reserved.

关键词： Object detection

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A Trajectory Tracking Algorithm Based on Interior Point Method for A Class of Mobile Manipulators

A Trajectory Tracking Algorithm Based on Interior Point Meth...

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Chinese automation Congress (CAC)

作者： Xuechen Rao Yahui Gan Xiaoteng Wang School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education NanJing China

At present, due to the high redundancy and strong coupling characteristics of mobile manipulator systems, there are few and in-depth studies on coordinated motion planning. Aiming at the above problems, this paper proposes a coordinated control algorithm that can track the desired trajectory of the end-effector based on a class of 5-DOF mobile manipulators. The algorithm takes the power consumption and trajectory stability of the entire system as the optimization objectives, and sets the function of the selected optimization objective on the desired trajectory, and performs optimization based on the interior point method of convex optimization to converge to the optimal solution faster. Finally, the system is simulated to verify the correctness and effectiveness of the control algorithm.

关键词： Smoothing methods Trajectory tracking Simulation Robot kinematics Redundancy Mathematical models End effectors

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Weighted Fusion of Multiple Classifiers for Human Activity Recognition 26

Weighted Fusion of Multiple Classifiers for Human Activity R...

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26th International Conference on Information Fusion, FUSION 2023

作者： Zuo, Kezhu Li, Xinde Dezert, Jean Dong, Yilin Southeast University School of Cyber Science and Engineering Nanjing China Southeast University Key Laboratory of Measurement and Control of Cse School of Automation Nanjing China The French Aerospace Lab Onera DTIS/MIDL Palaiseau France Shanghai Maritime University College of Computer Science and Engineering Shanghai China

ISBN: (纸本)9798890344854

Human Activity Recognition (HAR) based on wear-able device has become a hot topic of research due to its wide range of applications in health-care, fitness and smart homes. However, the classification of some activities with similar sensor readings, such as standing and sitting, is usually more challenging for the design of efficient activity recognition algorithms. Considering the inconsistent performance of different classifiers, which can provide information complementary for individual classifier, we propose a novel multi-classifier fusion method based on belief functions (BFs) theory for HAR. Specifically, at first, four classifiers are trained using time-domain and frequency-domain features to obtain basic belief assignments (BBA) of activity, respectively. Then, three assessment criteria are utilized to evaluate the reliability of the classifiers and a scoring matrix is constructed. Next, the algorithm of Belief Function based the Technique for Order Preference by Similarity to Ideal Solution (BF-TOPSIS) is employed to calculate the weighting coefficients for each classifier. Finally, the discounting and Dempster's rules are adopted to combine the multiple classifiers and further decision making. Several experiments were conducted to illustrate the performance of the proposed method using the UCI smartphone dataset, and the results show that the proposed method is more accurate than the state-of-art methods. © 2023 International Society of Information Fusion.

关键词： Frequency domain analysis

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Missing Small Bolt Detection on High-speed Train Using Improved Yolov5

Missing Small Bolt Detection on High-speed Train Using Impro...

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International Conference on systems and Informatics (ICSAI)

作者： Yiming Wei Xiaobo Lu School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9781665474498

Tiny bolts are widely used on high-speed trains, playing an important role in fixing train components. However, because of the complex running environment of trains, missing bolts occur from time to time and may cause traffic accidents, resulting in property damage and, in serious cases, endangering the lives of the occupants. Therefore, it is essential to detect missing bolts on high-speed trains. The bolts discussed in this paper are generally located on the underside of high-speed trains and their small size makes detection more difficult. In this paper, we first expand the dataset, and then add the Attention module and Transformer based on YOLOv5, and change the FPN of YOLOv5 to BiFPN, fuse the features of different layers using different weights, and crop the high-resolution original image during training and testing, and finally return to the original image. Our method eventually achieves 95.3% AP, effectively improving the detection accuracy.

关键词： Training Fuses Training data Object detection Fasteners Transformers Data models

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