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Chinese control and Decision Conference, CCDC

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

ISBN: (纸本)9781665478977

The partial shading condition (PSC) makes it challenging for the PV system to find the maximum power point. In this paper, an improved gray wolf algorithm (GWO) is proposed by introducing elimination mechanism, greedy mechanism and adjusting the convergence factor which overcomes the contradiction between global exploration ability and convergence time. Under fast varying irradiance and PSC, IGWO has been compared with GWO, particle swarm optimization (PSO), and adaptive particle swarm optimization (APSO), the results shows the superiority of IGWO in the MPPTs of the PV system.

关键词： Photovoltaic systems Maximum power point trackers Adaptive systems Heuristic algorithms Particle swarm optimization Oscillators Optimization

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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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第34届中国控制与决策会议

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

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

关键词： Lyapunov Adaptive Sliding Mode control for Force Tracking Using Nonlinear Observer

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TransTracking for UAV: An Autonomous Real-time Target Tracking System for UAV via Transformer Tracking

TransTracking for UAV: An Autonomous Real-time Target Tracki...

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2021 International Conference on Intelligent Technology and Embedded systems, ICITES 2021

作者： Sun, Xiaolou Xie, Fei Wang, Qi Yao, Yuncong Wang, Hao Wang, Wei Yang, Wankou School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Nanjing University of Information Science and Technology School of Automation Nanjing211800 China

ISBN: (纸本)9781665427555

Most of the existing Siamese-type trackers usually adopt pre-defined anchor boxes or anchor-free schemes to accurately estimate the bounding box of targets. Unfortunately, they suffer from complicated hand-designed components and tedious post-processings. It is not easy to adjust parameters for unique scenes in real applications. So, we propose a new scheme by formulating visual tracking as a direct set prediction problem to alleviate this issue. The main component is a transformer attached to the Siamese-type feature extraction networks. Thus, our new framework can be summarized as Siamese Network with Transformers (SiamTFR). With a fixed small set of learned object queries, we force the final set of predictions via bipartite matching, significantly reducing hyper-parameters associated with the candidate boxes. Due to the unique predictions of this framework, we significantly ease the heavy burden of hyper-parameters search of post-processings in visual tracking. Extensive experiments on visual tracking benchmarks, including GOT-10K, demonstrate that SiamTFR achieves competitive performance and runs at 50 FPS. Specifically, SiamTFR outperforms leading anchor-based tracker SiamRPN++ in the GOT-10K benchmark, confirming its effectiveness and efficiency. Furthermore, SiamTFR is deployed on the embedded device in which the algorithm can be run at 30FPS or 54FPS with TensorRT meeting the real-time requirements. In addition, we design the complete tracking system demo that can work in the real road to narrow the gap between the academic models and industrial deployments. © 2021 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Close-range Hot Spot Detection based on K-neighbor Algorithm and Experiment on Hot Spot Effect 4

Close-range Hot Spot Detection based on K-neighbor Algorithm...

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

作者： Na, ZhiXiong Wang, Dong Wang, ZiYue Wang, Jian Tang, Yu Zhang, ZiHan State Grid e-commerce Co. Ltd Beijing100053 China State Grid Tianjin Electric Power Company China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China

Abnormalities caused by the hot spot effect are very common in the application of photovoltaic modules, which seriously affect the life and power generation efficiency of photovoltaic modules. Therefore, the study of hot spot effect is of great significance to the development of photovoltaic industry in the future. By analyzing the hot spot effect and its causes, this paper lists possible factors that may affect the hot spot effect, uses the K-proximity algorithm for hot spot detection to classify the near-field infrared images obtained in photovoltaic power plants, and designs experiments to explore the influence of several factors on the hot spot effect, the influence characteristics of the shading area and the types of shading objects are deeply explored, and finally a certain summary is made. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Infrared imaging

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Extraction of main factors affecting muscle fatigue in lower-limb rehabilitation 41

Extraction of main factors affecting muscle fatigue in lower...

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第41届中国控制会议

作者： Tiecheng Liu Rennong Wang Jinhua She Juan Zhao Hiroshi Hashimoto Daisuke Chugo Graduate School of Engineering Tokyo University of Technology School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Industrial Technology Advanced Institute of Industrial Technology Graduate School of Science and Technology Kwansei Gakuin University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This study extracted the main factors from a questionnaire,measurement results,and the analysis of sEMG signals to establish a method of evaluating muscle *** measured factors(rating of perceived exertion,heart rate,mileage) and five factors obtained from the analysis of sEMG signals(root mean square,mean absolute value,variance,times of zero crossing,median frequency) were *** the F-test,the correlation analysis,and the principal component analysis,we finally extracted six factors as the main factors that have a big influence on muscle fatigue.

关键词： correlation analysis F-test lower-limb rehabilitation muscle fatigue principal component analysis rehabilitation statistical analysis surface electromyography(sEMG)

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A Method of Touchable 3d Model Reconstruction based on Mixed Reality -A Case Study of Medical Training Applications 23

A Method of Touchable 3d Model Reconstruction based on Mixed...

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6th International Conference on Image and Graphics Processing, ICIGP 2023

作者： Liu, Mingyang Guo, Dalei Zhang, Zhicheng The School of Artificial Intelligence University of Chinese Academy of Sciences China The State Key Lab. of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China Department of Orthopedic The 7th Medical Center of PLA General Hospital China

ISBN: (纸本)9781450398572

The application of trauma and hemorrhage medical treatment training has generated higher and higher requirements for the authenticity of the medical model. With the increasing integration of mixed reality technology and the medical field, multi-view-based 3D reconstruction technology can generate trauma medical object models not limited to specific targets, with low cost and high precision. However, the current reconstruction methods have weak points such as the inability to build the object surface beyond the direct view of humans, the uneven distribution of reconstructed point clouds, many holes, and reconstructed triangles. And it is time-consuming and laborious to fill and modify manually and requires highly skilled modeling expertise. Therefore, the models generated by traditional 3D reconstruction methods cannot meet the needs of interaction and touch in mixed reality applications. In order to solve these problems, we propose a new model generation method based on multi-view and point cloud processing, which enables the model to reduce the computational cost under the premise of meeting the need for direct interaction and touch in mixed reality applications. Finally, based on the reconstruction method proposed in this paper, a new medical trauma hemorrhage control and rescue training system is designed and implemented, which proves the effectiveness of the method proposed in this paper. © 2023 Owner/Author.

关键词： Mixed reality

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Enabling few-shot learning with PID control: a layer adaptive optimizer 24

Enabling few-shot learning with PID control: a layer adaptiv...

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Proceedings of the 41st International Conference on Machine Learning

作者： Le Yu Xinde Li Pengfei Zhang Zhentong Zhang Fir Dunkin School of Automation Southeast University Nanjing China and Nanjing Center for Applied Mathematics Nanjing China and Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China School of Automation Southeast University Nanjing China and Nanjing Center for Applied Mathematics Nanjing China and Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China and Southeast University Shenzhen Research Institute Shenzhen China School of Automation Southeast University Nanjing China and Nanjing Center for Applied Mathematics Nanjing China

Model-Agnostic Meta-Learning (MAML) and its variants have shown remarkable performance in scenarios characterized by a scarcity of labeled data during the training phase of machine learning models. Despite these successes, MAMLbased approaches encounter significant challenges when there is a substantial discrepancy in the distribution of training and testing tasks, resulting in inefficient learning and limited generalization across domains. Inspired by classical proportional-integral-derivative (PID) control theory, this study introduces a Layer-Adaptive PID (LA-PID) Optimizer, a MAML-based optimizer that employs efficient parameter optimization methods to dynamically adjust task-specific PID control gains at each layer of the network, conducting a first-principles analysis of optimal convergence conditions. A series of experiments conducted on four standard benchmark datasets demonstrate the efficacy of the LA-PID optimizer, indicating that LA-PID achieves state-of-the-art performance in few-shot classification and cross-domain tasks, accomplishing these objectives with fewer training steps. Code is available on https://***/yuguopin/LA-PID.

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Adaptive tracking control of high-order MIMO nonlinear systems with prescribed performance

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Frontiers of Information Technology & Electronic engineering 2021年第7期22卷 986-1001页

作者： Xuerao WANG Qingling WANG Changyin SUN School of Automation Southeast UniversityNanjing 210096China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast UniversityNanjing 210096China

In this paper,an observer-based adaptive prescribed performance tracking control scheme is developed for a class of uncertain multi-input multi-output nonlinear systems with or without input saturation.A novel finite-time neural network disturbance observer is constructed to estimate the system uncertainties and external *** guarantee the prescribed performance,an error transformation is applied to transfer the time-varying constraints into a constant ***,by employing a barrier Lyapunov function and the backstepping technique,an observer-based tracking control strategy is *** is proven that using the proposed algorithm,all the closedloop signals are bounded,and the tracking errors satisfy the predefined time-varying performance ***,simulation results on a quadrotor system are given to illustrate the effectiveness of the proposed control scheme.

关键词： Adaptive tracking control Prescribed performance Input saturation Disturbance observer Neural network

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MFANet: Mixed Feature Attention Network for Port Lane Detection

MFANet: Mixed Feature Attention Network for Port Lane Detect...

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Chinese control Conference (CCC)

作者： Jinwei Zhang Jinya Su Dewei Yi Jun Yang Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education and the School of Automation Southeast University Nanjing China Department of Computing Science University of Aberdeen Aberdeen U.K.

With the advancement of industrial automation and artificial intelligence technology, unmanned port autonomy has gained increasing attention. Port automatic driving technology is a critical component of unmanned autonomous systems, enabling rubber tire gantry cranes (RTGs) to autonomously navigate by detecting port lanes and implementing control commands. In this study, a deep learning-based method is proposed for detecting port lanes in complex port scenes. The method employs the Inception module and attention mechanism to enhance lane feature extraction, and a structural loss is introduced to explicitly constrain the detection results and incorporate the prior characteristics of port lanes. A novel Mixed Feature Attention Network (MFANet) is proposed to implement the method for port lane detection. Experimental results demonstrate that MFANet effectively improves the accuracy of port lane detection while maintaining high computational efficiency. Furthermore, the performance of MFANet is evaluated in a real-world application scenario.

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Finite-Time Observer Based Integral Terminal SMC for Converter-Driven Motor systems with Mismatched Disturbances

Finite-Time Observer Based Integral Terminal SMC for Convert...

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Chinese automation Congress (CAC)

作者： Zhongding Zhang Zeyu Guo Zuo Wang Shihua Li School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Shenzhen Research Institute Southeast University Shenzhen China

Converter-driven motor systems play crucial roles in contemporary industrial applications owning to the advantages of smooth starting and stepless speed regulation. For such fourth-order systems with both immeasurable states and mismatched disturbances, a finite-time control solution is proposed to address the speed tracking problem in this paper. Firstly, a finite-time observer is constructed to precisely estimate the immeasurable states and mismatched disturbances. Then, based on integral terminal sliding mode control (ITSMC), a continuous finite-time controller is designed for the systems to achieve both rapid response and superior speed tracking performance. Furthermore, a rigorous global finite-time stability analysis for the closed-loop system is presented. Finally, simulation results validate the effectiveness of the proposed control method. As compared with existing methods, the composite ITSMC algorithm design demonstrates reliable finite-time speed tracking performance and exceptional capability in disturbance rejection.

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