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10th International Conference on systems and Informatics, ICSAI 2024

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

ISBN: (纸本)9798331510138

Joint face super-resolution and frontalization of non-frontal low-resolution faces is of significant importance for many face analysis applications. However, at the same time, it is a challenging task. In this paper, a novel Guided Transformative Generative Adversarial Network (GT-GAN) is proposed to address the challenge of generating frontal high-resolution face images from non-frontal low-resolution face images. Existing methods usually treat super-resolution and frontalization as two separate tasks, leading to unsatisfactory processing results. GTG AN innovatively achieves both goals within a unified frame-work. Specifically, we propose Profile Attention Guidance (PAG) to generate landmark heatmaps that provide a priori pose information to the generative network and direct its attention to critical facial regions. In addition, an Attention Fusion Transformation Module (AFTM) is proposed to significantly improve the hallucination performance of the network by utilizing the attention mechanism and STNs, combined with sequential feature enhancement strategies. The experimental results show that GT-GAN exhibits superior performance in the joint face super-resolution and frontalization task on the public face dataset Multi-PIE, which provides new ideas and references for this challenging topic. © 2024 IEEE.

关键词： Generative adversarial networks

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New control Paradigm for Industry 5.0:From Big Models to Foundation control and Management

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1643-1646页

作者： Fei-Yue Wang IEEE the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China

DO we need a fundamental change in our professional culture and knowledge foundation for control and automation?If so,what are necessary and critical steps we must take to ensure such a change would take place effecti... 详细信息

关键词： smoothly steps culture

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Hazard-Aware Weighted Advantage Combination for UAV Target Tracking and Obstacle Avoidance

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IEEE/CAA Journal of Automatica Sinica 2024年第6期12卷 1260-1271页

作者： Xu, Lele Liu, Jian Chang, Xiaoguang Liu, Xuping Sun, Changyin The School of Artificial Intelligence Anhui University Hefei230601 China The School of Automation the Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China

In recent years, the rapid evolution of unmanned aerial vehicles (UAVs) has brought about transformative changes across various industries. However, addressing fundamental challenges in UAV technology, particularly target tracking and obstacle avoidance, remains crucial for wildlife protection, military industry security, etc. Many existing methods based on reinforcement learning to solve UAV multi-tasks need to be redesigned and retrained, and cannot be quickly and effectively extended to other scenarios. To this end, we propose a novel solution based on a hazard-aware weighted advantage combination for UAV target tracking and obstacle avoidance. First, we independently trained the UAV target tracking and obstacle avoidance using the Dueling Double Deep Q-Network reinforcement learning algorithm. Subsequently, in a multitasking scenario, we introduce the two pre-trained networks. Meanwhile, we design a weight determined by the present risk level encountered by the UAV. This weight is utilized to perform a weighted summation of the advantage values from both networks, eliminating the need for retraining to obtain the final action. We validate our approach through extensive simulation experiments in the robotics simulator known as CoppeliaSim. The results demonstrate that our method outperforms current state-of-the-art techniques, achieving superior performance in both tracking accuracy and avoidance of collisions. © 2013 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Optimal Deployment of Target Localization With Distance-Dependent Noise

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IEEE Internet of Things Journal 2025年第12期12卷 20959-20972页

作者： Tian, Junxi Yang, Ming Chao, Tao Harbin Institute of Technology Control and Simulation Center National Key Laboratory of Modeling and Simulation for Complex Systems Harbin150001 China

The cooperative localization of radio-based distance measurement is one of the methods to effectively suppress the nonline of sight (NLOS) ranging errors and as a complement to visual/global navigation satellite system (GNSS) localization for unmanned aerial vehicle (UAV) in GNSS challenging or denied environments due to its motility. Target localization can be regarded as a special case of cooperative localization. Meanwhile, the UAV can be considered as a ranging node when the ranging terminal is rigidly mounted on the UAV. To improve the target localization accuracy, the optimal deployment of anchor UAVs is one of the factors we consider when the noise characteristics are different. In this paper, the range-dependent noise in a real flight environment is considered and modeled separately according to the difference in noise characteristics. Subsequently, based on this correlation model, the Fisher information matrix (FIM) and a cost function derived from the A-optimal criterion are provided. Finally, the optimal deployment conditions and the minimum mean square error (MMSE) can be derived by minimizing the cost function as the objective. Through simulation and localization experiments, the validity of the optimal deployment conditions and the corresponding MMSE are verified. Meanwhile, it is concluded that when the noise is range-dependent, it will not affect the optimal deployment result but will significantly change the value of MMSE. © 2014 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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HarmonyNav: Robot Navigation in Human-Robot Coexistence Environment Considering Group and Pedestrian Intentions

HarmonyNav: Robot Navigation in Human-Robot Coexistence Envi...

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2024 Jiangsu Annual Conference on Automation, JACA 2024

作者： Wang, Yutao Fang, Fang Liu, Chenyang Fan, Tao Li, Yi The Key Laboratory of Measurement and Control of Complex Systems of Engineering School of Automation Southeast University Ministry of Education Nanjing210096 China

ISBN: (纸本)9781837242689

Service robots must navigate efficiently and harmoniously in human-robot coexistence environments. Previous studies often treated pedestrians as independent entities, ignoring human intentions and leading to group intersections and performance issues. We introduce HarmonyNav, a crowd navigation algorithm that enhances human-robot harmony. Our method uses Human-Robot Interaction sub-networks to account for indirect group impacts on pedestrians and predicts pedestrian trajectories to infer intentions. Employing proximal policy optimization (PPO) in reinforcement learning, we develop a harmonious navigation policy. In simulation experiments, our results show improved navigation performance, reducing group intersections and individual intrusions. © The Institution of Engineering & Technology 2024.

关键词： Reinforcement learning

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Prescribed-Time Nash Equilibrium Seeking for Pursuit-Evasion Game

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1518-1520页

作者： Lei Xue Jianfeng Ye Yongbao Wu Jian Liu D.C.Wunsch Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationNanjing 210096 School of Automation Southeast UniversityNanjing 210096China Department of Electrical and Computer Engineering Missouri University of Science and TechnologyRollaMO 65409 USA IEEE

Dear Editor,This letter is concerned with prescribed-time Nash equilibrium(PTNE)seeking problem in a pursuit-evasion game(PEG)involving agents with second-order *** order to achieve the prior-given and user-defined convergence time for the PEG,a PTNE seeking algorithm has been developed to facilitate collaboration among multiple pursuers for capturing the evader without the need for any global ***,it is theoretically proved that the prescribedtime convergence of the designed algorithm for achieving Nash equilibrium of ***,the effectiveness of the PTNE method was validated by numerical simulation results.A PEG consists of two groups of agents:evaders and *** pursuers aim to capture the evaders through cooperative efforts,while the evaders strive to evade *** is a classic noncooperative *** has attracted plenty of attention due to its wide application scenarios,such as smart grids[1],formation control[2],[3],and spacecraft rendezvous[4].It is noteworthy that most previous research on seeking the Nash equilibrium of the game,where no agent has an incentive to change its actions,has focused on asymptotic and exponential convergence[5]-[7].

关键词： seeking prescribed convergence

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Collision-free and Effecient Robotic Grasping based on Hierarchical Reinforcement Learning

Collision-free and Effecient Robotic Grasping based on Hiera...

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2024 Jiangsu Annual Conference on Automation, JACA 2024

作者： Li, Yi Fang, Fang Liu, Chenyang Wang, Yutao Fan, Tao School of Automation Southeast University China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9781837242689

In the realm of robotics, grasping within unstructured environments has consistently been a challenging task. Direct grasping often results in failures due to collisions, and some pre-grasping maneuvers can eliminate the tightly stacked state between objects, thereby enhancing the success rate of grasping. In this paper, we opt for pushing as a pre-grasping maneuver. We propose a deep Q-network with a fused convolutional feature enhancement module to improve action value estimation, enhancing the robot’s pushing and grasping abilities. Additionally, a hierarchical reinforcement learning framework optimizes action sequences for better synergy between pushing and grasping. In simulated experiments, the model achieved a high grasp success rate with just a few hours of training, outperforming other methods in the literature. © The Institution of Engineering & Technology 2024.

关键词： Adversarial machine learning

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A Model-Based Unmatched Disturbance Rejection control Approach for Speed Regulation of a Converter-Driven DC Motor Using Output-Feedback

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IEEE/CAA Journal of Automatica Sinica 2022年第2期9卷 365-376页

作者： Lu Zhang Jun Yang Shihua Li School of Automation Southeast UniversityKey Laboratory of Measurement and Control of Complex Systems of EngineeringMinistry of Education IEEE Department of Aeronautical and Automotive Engineering Loughborough University

The speed regulation problem with only speed measurement is investigated in this paper for a permanent magnet direct current(DC)motor driven by a buck *** lumping all unknown matched/unmatched disturbances and uncertainties together,the traditional active disturbance rejection control(ADRC)approach provides an intuitive solution for the problem under ***,for such a higher-order disturbed system,the increase of poles for the extended state observer(ESO)therein will lead to drastically growth of observer gains,which causes severe noise *** paper aims to propose a new model-based disturbance rejection controller for the converter-driven DC motor system using *** of estimating lumped disturbances directly,a new observer is constructed to estimate the desired steady state of control signal as well as errors between the real states and their desired steady-state ***,a controller with only speed measurement is proposed by utilizing the *** performance of the proposed method is tested through experiments on *** is further shown via numerical calculations and experimental results that the poles of the observer within the proposed control approach can be largely increased without significantly increasing magnitude of the observer gains.

关键词： Bandwidth widening converter-driven direct current(DC)motor disturbance observer model-based disturbance rejection speed regulation

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Design of low-power, high-precision wireless temperature transmitter based on wifi

Design of low-power, high-precision wireless temperature tra...

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2023 Jiangsu Annual Conference on Automation, JACA 2023

作者： Wang, Lening Wang, Xiaojun Jiang, Rongfu Gao, Yifeng Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China

ISBN: (纸本)9781839539848

In order to enhance the performance of temperature transmitters and facilitate their integration into intelligent and wireless systems, a novel design is proposed, incorporating a pseudo self-balancing electric bridge to achieve a high-precision and wide-range temperature measurement capability. This advanced transmitter not only maximizes the measurement range of thermal resistance but also ensures exceptional temperature accuracy. It seamlessly transfers data to a server through the utilization of the WIFI protocol. Furthermore, the transmitter is equipped with wireless communication capabilities, allowing data transmission through a 4-20mA current loop. The calibration and configuration processes can be conveniently carried out via a USB interface. Rigorous testing validates that the accuracy of the transmitter conforms to the stringent specifications outlined in GB/T 34072-2017 for 0.1-level temperature transmitters. Additionally, when operated with battery power, the transmitter exhibits commendably low average power consumption. © The Institution of Engineering & Technology 2023.

关键词： Transmitters

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Design and Hardware-in-the-loop Validation:A Fractional Full Feed-forward Method for Grid Voltage in LCL Grid-connected Inverter systems

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CSEE Journal of Power and Energy systems 2023年第5期9卷 1720-1731页

作者： Qingyi Wang Binlei Ju Yudi Lei Dan Zhou Shuai Yin Danyun Li the School of Automation China University of Geosciencesand Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex SystemsWuhan 430074China.

The harmonic disturbance in the background grid is a problem that must be considered in the design of a gridconnected ***,the full feed-forward method cannot completely suppress the harmonic disturbance in theory and is sensitive to *** tackle these problems,a fractional full feed-forward method of grid voltage is proposed in this ***,the mathematical model of the full feed-forward method is deduced,and the differences with the theoretical solution,which can suppress all harmonics,are ***,the parameter equation,the harmonic suppression performance,stability analysis and the implementation process of this method are *** with the full feed-forward method,the proposed method not only further improves the harmonic suppression performance,but also reduces the order of the mathematical model of the differential term in the feed-forward *** addition,the proposed method can be used to flexibly design feed-forward coefficients by selecting the order of suppressed ***,the proposed method is validated by a hardware-in-the-loop experiment on a MT real-time control platform NI PXIE-1071.

关键词： Fractional differential full feed-forward method hardware-in-the-loop LCL inverter

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